Patent Application
20250240409
Embodiments of the present disclosure relates generally to video processing techniques, and more particularly, to motion candidate list construction.
In nowadays, digital video capabilities are being applied in various aspects of peoples' lives. Multiple types of video compression technologies, such as MPEG-2, MPEG-4, ITU-TH.263, ITU-TH.264/MPEG-4 Part 10 Advanced Video Coding (AVC), ITU-TH.265 high efficiency video coding (HEVC) standard, versatile video coding (VVC) standard, have been proposed for video encoding/decoding. However, coding efficiency of video coding techniques is generally expected to be further improved.
Embodiments of the present disclosure provide a solution for video processing.
In a first aspect, a method for video processing is proposed. The method comprises: determining, for a conversion between a current video block of a video and a bitstream of the video, a plurality of motion vector prediction (MVP) candidates of the current video block; determining a candidate list of the current video block by applying a plurality of pruning processes to the plurality of MVP candidates; and performing the conversion based on the candidate list. The method in accordance with the first aspect of the present disclosure determines the candidate list of the current video block by applying a plurality of pruning processes, and thus can avoid redundant candidate in the candidate list and improve the diversity of the candidate list. In this way, the coding efficiency and coding effectiveness can be improved.
In a second aspect, an apparatus for video processing is proposed. The apparatus comprises a processor and a non-transitory memory with instructions thereon. The instructions upon execution by the processor, cause the processor to perform a method in accordance with the first aspect of the present disclosure.
In a third aspect, a non-transitory computer-readable storage medium is proposed. The non-transitory computer-readable storage medium stores instructions that cause a processor to perform a method in accordance with the first aspect of the present disclosure.
In a fourth aspect, another non-transitory computer-readable recording medium is proposed. The non-transitory computer-readable recording medium stores a bitstream of a video which is generated by a method performed by an apparatus for video processing. The method comprises: determining a plurality of motion vector prediction (MVP) candidates of a current video block of the video; determining a candidate list of the current video block by applying a plurality of pruning processes to the plurality of MVP candidates; and generating the bitstream based on the candidate list.
In a fifth aspect, a method for storing a bitstream of a video is proposed. The method comprises: determining a plurality of motion vector prediction (MVP) candidates of a current video block of the video; determining a candidate list of the current video block by applying a plurality of pruning processes to the plurality of MVP candidates; generating the bitstream based on the candidate list; and storing the bitstream in a non-transitory computer-readable recording medium.
This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Through the following detailed description with reference to the accompanying drawings, the above and other objectives, features, and advantages of example embodiments of the present disclosure will become more apparent. In the example embodiments of the present disclosure, the same reference numerals usually refer to the same components.
Throughout the drawings, the same or similar reference numerals usually refer to the same or similar elements.
Principle of the present disclosure will now be described with reference to some embodiments. It is to be understood that these embodiments are described only for the purpose of illustration and help those skilled in the art to understand and implement the present disclosure, without suggesting any limitation as to the scope of the disclosure. The disclosure described herein can be implemented in various manners other than the ones described below.
In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skills in the art to which this disclosure belongs.
References in the present disclosure to “one embodiment,” “an embodiment,” “an example embodiment,” and the like indicate that the embodiment described may include a particular feature, structure, or characteristic, but it is not necessary that every embodiment includes the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an example embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
It shall be understood that although the terms “first” and “second” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and similarly, a second element could be termed a first element, without departing from the scope of example embodiments. As used herein, the term “and/or” includes any and all combinations of one or more of the listed terms.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises”, “comprising”, “has”, “having”, “includes” and/or “including”, when used herein, specify the presence of stated features, elements, and/or components etc., but do not preclude the presence or addition of one or more other features, elements, components and/or combinations thereof.
The video source 112 may include a source such as a video capture device. Examples of the video capture device include, but are not limited to, an interface to receive video data from a video content provider, a computer graphics system for generating video data, and/or a combination thereof.
The video data may comprise one or more pictures. The video encoder 114 encodes the video data from the video source 112 to generate a bitstream. The bitstream may include a sequence of bits that form a coded representation of the video data. The bitstream may include coded pictures and associated data. The coded picture is a coded representation of a picture. The associated data may include sequence parameter sets, picture parameter sets, and other syntax structures. The I/O interface 116 may include a modulator/demodulator and/or a transmitter. The encoded video data may be transmitted directly to destination device 120 via the I/O interface 116 through the network 130A. The encoded video data may also be stored onto a storage medium/server 130B for access by destination device 120.
The destination device 120 may include an I/O interface 126, a video decoder 124, and a display device 122. The I/O interface 126 may include a receiver and/or a modem. The I/O interface 126 may acquire encoded video data from the source device 110 or the storage medium/server 130B. The video decoder 124 may decode the encoded video data. The display device 122 may display the decoded video data to a user. The display device 122 may be integrated with the destination device 120, or may be external to the destination device 120 which is configured to interface with an external display device.
The video encoder 114 and the video decoder 124 may operate according to a video compression standard, such as the High Efficiency Video Coding (HEVC) standard, Versatile Video Coding (VVC) standard and other current and/or further standards.
The video encoder 200 may be configured to implement any or all of the techniques of this disclosure. In the example of
In some embodiments, the video encoder 200 may include a partition unit 201, a predication unit 202 which may include a mode select unit 203, a motion estimation unit 204, a motion compensation unit 205 and an intra-prediction unit 206, a residual generation unit 207, a transform unit 208, a quantization unit 209, an inverse quantization unit 210, an inverse transform unit 211, a reconstruction unit 212, a buffer 213, and an entropy encoding unit 214.
In other examples, the video encoder 200 may include more, fewer, or different functional components. In an example, the predication unit 202 may include an intra block copy (IBC) unit. The IBC unit may perform predication in an IBC mode in which at least one reference picture is a picture where the current video block is located.
Furthermore, although some components, such as the motion estimation unit 204 and the motion compensation unit 205, may be integrated, but are represented in the example of
The partition unit 201 may partition a picture into one or more video blocks. The video encoder 200 and the video decoder 300 may support various video block sizes.
The mode select unit 203 may select one of the coding modes, intra or inter, e.g., based on error results, and provide the resulting intra-coded or inter-coded block to a residual generation unit 207 to generate residual block data and to a reconstruction unit 212 to reconstruct the encoded block for use as a reference picture. In some examples, the mode select unit 203 may select a combination of intra and inter predication (CIIP) mode in which the predication is based on an inter predication signal and an intra predication signal. The mode select unit 203 may also select a resolution for a motion vector (e.g., a sub-pixel or integer pixel precision) for the block in the case of inter-predication.
To perform inter prediction on a current video block, the motion estimation unit 204 may generate motion information for the current video block by comparing one or more reference frames from buffer 213 to the current video block. The motion compensation unit 205 may determine a predicted video block for the current video block based on the motion information and decoded samples of pictures from the buffer 213 other than the picture associated with the current video block.
The motion estimation unit 204 and the motion compensation unit 205 may perform different operations for a current video block, for example, depending on whether the current video block is in an I-slice, a P-slice, or a B-slice. As used herein, an “I-slice” may refer to a portion of a picture composed of macroblocks, all of which are based upon macroblocks within the same picture. Further, as used herein, in some aspects, “P-slices” and “B-slices” may refer to portions of a picture composed of macroblocks that are not dependent on macroblocks in the same picture.
In some examples, the motion estimation unit 204 may perform uni-directional prediction for the current video block, and the motion estimation unit 204 may search reference pictures of list 0 or list 1 for a reference video block for the current video block. The motion estimation unit 204 may then generate a reference index that indicates the reference picture in list 0 or list 1 that contains the reference video block and a motion vector that indicates a spatial displacement between the current video block and the reference video block. The motion estimation unit 204 may output the reference index, a prediction direction indicator, and the motion vector as the motion information of the current video block. The motion compensation unit 205 may generate the predicted video block of the current video block based on the reference video block indicated by the motion information of the current video block.
Alternatively, in other examples, the motion estimation unit 204 may perform bi-directional prediction for the current video block. The motion estimation unit 204 may search the reference pictures in list 0 for a reference video block for the current video block and may also search the reference pictures in list 1 for another reference video block for the current video block. The motion estimation unit 204 may then generate reference indexes that indicate the reference pictures in list 0 and list 1 containing the reference video blocks and motion vectors that indicate spatial displacements between the reference video blocks and the current video block. The motion estimation unit 204 may output the reference indexes and the motion vectors of the current video block as the motion information of the current video block. The motion compensation unit 205 may generate the predicted video block of the current video block based on the reference video blocks indicated by the motion information of the current video block.
In some examples, the motion estimation unit 204 may output a full set of motion information for decoding processing of a decoder. Alternatively, in some embodiments, the motion estimation unit 204 may signal the motion information of the current video block with reference to the motion information of another video block. For example, the motion estimation unit 204 may determine that the motion information of the current video block is sufficiently similar to the motion information of a neighboring video block.
In one example, the motion estimation unit 204 may indicate, in a syntax structure associated with the current video block, a value that indicates to the video decoder 300 that the current video block has the same motion information as the another video block.
In another example, the motion estimation unit 204 may identify, in a syntax structure associated with the current video block, another video block and a motion vector difference (MVD). The motion vector difference indicates a difference between the motion vector of the current video block and the motion vector of the indicated video block. The video decoder 300 may use the motion vector of the indicated video block and the motion vector difference to determine the motion vector of the current video block.
As discussed above, video encoder 200 may predictively signal the motion vector. Two examples of predictive signaling techniques that may be implemented by video encoder 200 include advanced motion vector predication (AMVP) and merge mode signaling.
The intra prediction unit 206 may perform intra prediction on the current video block. When the intra prediction unit 206 performs intra prediction on the current video block, the intra prediction unit 206 may generate prediction data for the current video block based on decoded samples of other video blocks in the same picture. The prediction data for the current video block may include a predicted video block and various syntax elements.
The residual generation unit 207 may generate residual data for the current video block by subtracting (e.g., indicated by the minus sign) the predicted video block(s) of the current video block from the current video block. The residual data of the current video block may include residual video blocks that correspond to different sample components of the samples in the current video block.
In other examples, there may be no residual data for the current video block for the current video block, for example in a skip mode, and the residual generation unit 207 may not perform the subtracting operation.
The transform processing unit 208 may generate one or more transform coefficient video blocks for the current video block by applying one or more transforms to a residual video block associated with the current video block.
After the transform processing unit 208 generates a transform coefficient video block associated with the current video block, the quantization unit 209 may quantize the transform coefficient video block associated with the current video block based on one or more quantization parameter (QP) values associated with the current video block.
The inverse quantization unit 210 and the inverse transform unit 211 may apply inverse quantization and inverse transforms to the transform coefficient video block, respectively, to reconstruct a residual video block from the transform coefficient video block. The reconstruction unit 212 may add the reconstructed residual video block to corresponding samples from one or more predicted video blocks generated by the predication unit 202 to produce a reconstructed video block associated with the current video block for storage in the buffer 213.
After the reconstruction unit 212 reconstructs the video block, loop filtering operation may be performed to reduce video blocking artifacts in the video block.
The entropy encoding unit 214 may receive data from other functional components of the video encoder 200. When the entropy encoding unit 214 receives the data, the entropy encoding unit 214 may perform one or more entropy encoding operations to generate entropy encoded data and output a bitstream that includes the entropy encoded data.
The video decoder 300 may be configured to perform any or all of the techniques of this disclosure. In the example of
In the example of
The entropy decoding unit 301 may retrieve an encoded bitstream. The encoded bitstream may include entropy coded video data (e.g., encoded blocks of video data). The entropy decoding unit 301 may decode the entropy coded video data, and from the entropy decoded video data, the motion compensation unit 302 may determine motion information including motion vectors, motion vector precision, reference picture list indexes, and other motion information. The motion compensation unit 302 may, for example, determine such information by performing the AMVP and merge mode. AMVP is used, including derivation of several most probable candidates based on data from adjacent PBs and the reference picture. Motion information typically includes the horizontal and vertical motion vector displacement values, one or two reference picture indices, and, in the case of prediction regions in B slices, an identification of which reference picture list is associated with each index. As used herein, in some aspects, a “merge mode” may refer to deriving the motion information from spatially or temporally neighboring blocks.
The motion compensation unit 302 may produce motion compensated blocks, possibly performing interpolation based on interpolation filters. Identifiers for interpolation filters to be used with sub-pixel precision may be included in the syntax elements.
The motion compensation unit 302 may use the interpolation filters as used by the video encoder 200 during encoding of the video block to calculate interpolated values for sub-integer pixels of a reference block. The motion compensation unit 302 may determine the interpolation filters used by the video encoder 200 according to the received syntax information and use the interpolation filters to produce predictive blocks.
The motion compensation unit 302 may use at least part of the syntax information to determine sizes of blocks used to encode frame(s) and/or slice(s) of the encoded video sequence, partition information that describes how each macroblock of a picture of the encoded video sequence is partitioned, modes indicating how each partition is encoded, one or more reference frames (and reference frame lists) for each inter-encoded block, and other information to decode the encoded video sequence. As used herein, in some aspects, a “slice” may refer to a data structure that can be decoded independently from other slices of the same picture, in terms of entropy coding, signal prediction, and residual signal reconstruction. A slice can either be an entire picture or a region of a picture.
The intra prediction unit 303 may use intra prediction modes for example received in the bitstream to form a prediction block from spatially adjacent blocks. The inverse quantization unit 304 inverse quantizes, i.e., de-quantizes, the quantized video block coefficients provided in the bitstream and decoded by entropy decoding unit 301. The inverse transform unit 305 applies an inverse transform.
The reconstruction unit 306 may obtain the decoded blocks, e.g., by summing the residual blocks with the corresponding prediction blocks generated by the motion compensation unit 302 or intra-prediction unit 303. If desired, a deblocking filter may also be applied to filter the decoded blocks in order to remove blockiness artifacts. The decoded video blocks are then stored in the buffer 307, which provides reference blocks for subsequent motion compensation/intra predication and also produces decoded video for presentation on a display device.
Some exemplary embodiments of the present disclosure will be described in detailed hereinafter. It should be understood that section headings are used in the present document to facilitate ease of understanding and do not limit the embodiments disclosed in a section to only that section. Furthermore, while certain embodiments are described with reference to Versatile Video Coding or other specific video codecs, the disclosed techniques are applicable to other video coding technologies also. Furthermore, while some embodiments describe video coding steps in detail, it will be understood that corresponding steps decoding that undo the coding will be implemented by a decoder. Furthermore, the term video processing encompasses video coding or compression, video decoding or decompression and video transcoding in which video pixels are represented from one compressed format into another compressed format or at a different compressed bitrate.
This disclosure is related to video coding technologies. Specifically, it is about motion vector prediction (MVP) construction method in video coding. The ideas may be applied individually or in various combination, to any video coding standard or non-standard video codec.
The exponential increasing of multimedia data poses a critical challenge for video coding. To satisfy the increasing demands for more efficient compression technology, ITU-T and ISO/IEC have developed a series of video coding standards in the past decades. In particular, the ITU-T produced H.261 and H.263, ISO/IEC produced MPEG-1 and MPEG-4 visual, and the two organizations jointly developed the H.262/MPEG-2 Video, H.264/MPEG-4 Advanced Video Coding (AVC), H.265/HEVC and the latest VVC standards. Since H.262/MPEG-2, hybrid video coding framework is employed wherein in intra/inter prediction plus transform coding are utilized.
Inter prediction aims to remove the temporal redundancy between adjacent frames, which serves as an indispensable component in the hybrid video coding framework. Specifically, inter prediction makes use of the contents specified by motion vector (MV) as the predicted version of the current to-be-coded block, thus only residual signals and motion information are transmitted in the bitstream. To reduce the cost for MV signaling, motion vector prediction (MVP) came into being as an effective mechanism to convey motion information. Early strategies simply use the MV of a specified neighboring block or the median MV of neighboring blocks as MVP. In H.265/HEVC, competing mechanism was involved where the optimal MVP is selected from multiple candidates through rate distortion optimization (RDO). In particular, advanced MVP (AMVP) mode and merge mode are devised with different motion information signaling strategy. With the AMVP mode, a reference index, an MVP candidate index referring to an AMVP candidate list and motion vector difference (MVD) is signaled. Regarding the merge mode, only a merge index referring to a merge candidate list is signaled, and all the motion information associated with the merge candidate is inherited. Both AMVP mode and merge mode need to construct MVP candidate list, and the details of the construction process for these two modes are described as follows.
AMVP mode: AMVP exploits spatial-temporal correlation of motion vector with neighboring blocks, which is used for explicit transmission of motion parameters. For each reference picture list, a motion vector candidate list is constructed by firstly checking availability of left, above temporally neighboring positions, removing redundant candidates and adding zero vector to make the candidate list to be constant length. For spatial motion vector candidate derivation, two motion vector candidates are eventually derived based on motion vectors of blocks located in five different positions as depicted in
Merge mode: Similar to AMVP mode, MVP candidate list for merge mode comprises of spatial and temporal candidates as well. For spatial motion vector candidate derivation, at most four candidates are selected with order A1, B1, B0, A0 and B2 after performing availability and redundant checking. For temporal merge candidate (TMVP) derivation, at most one candidate is selected from two temporal neighboring blocks (C0 and C1). When there are not enough merge candidates with spatial and temporal candidates, combined bi-predictive merge candidates and zero MV candidates are added to MVP candidate list. Once the number of available merge candidates reaches the signaled maximally allowed number, the merge candidate list construction process is terminated.
In VVC, the construction process for merge mode is further improved by introducing the history-based MVP (HMVP), which incorporates the motion information of previously coded blocks which may be far away from current block. In VVC, HMVP merge candidates are appended to merge list after the spatial MVP and TMVP. In this method, the motion information of a previously coded block is stored in a table and used as MVP for the current CU. The table with multiple HMVP candidates is maintained with first-in-first-out strategy during the encoding/decoding process. Whenever there is a non-subblock inter-coded CU, the associated motion information is added to the last entry of the table as a new HMVP candidate.
During the standardization of VVC, Non-adjacent MVP was proposed to facilitate better motion information derivation by exploiting the non-adjacent area. In ECM software, Non-adjacent MVP are inserted between TMVP and HMVP, where the distances between non-adjacent spatial candidates and current coding block are based on the width and height of current coding block as depicted in
In VVC, interpolations filters are used in both intra and inter coding process. Intra coding takes advantage of interpolation filters to generate fractional positions in angular prediction modes. In HEVC, a two-tap linear interpolation filter has been used to generate the intra prediction block in the directional prediction modes (i.e., excluding Planar and DC predictors). While in VVC, four-tap intra interpolation filters are utilized to improve the angular intra prediction accuracy. In particular, two sets of 4-tap interpolation filters are utilized in VVC intra coding, which are DCT-based interpolation filter (DCTIF) and smoothing interpolation filter (SIF). The DCTIF is constructed in the same way as the one used for chroma component motion compensation in both HEVC and VVC. The SIF is obtained by convolving the 2-tap linear interpolation filter with [1 2 1]/4 filter.
In VVC, the highest precision of explicitly signaled motion vectors is quarter-luma-sample. In some inter prediction modes such as the affine mode, motion vectors are derived at 1/16th-luma-sample precision and motion compensated prediction is performed at 1/16th-sample-precision. VVC allows different MVD precision ranging from 1/16-luma-sample to 4-luma-sample. For half-luma-sample precision, 6-tap interpolation filter is used. While for other fractional precisions, default 8-tap filter is used. Besides, the bilinear interpolation filter is used to generate the fractional samples for the searching process of decoder side motion vector refinement (DMVR) in VVC.
Template matching (TM) merge/AMVP mode is a decoder-side MV derivation method to refine the motion information of the current CU by finding the closest match between a template (i.e., top and/or left neighboring blocks of the current CU) in the current picture and a block (i.e., same size to the template) in a reference picture. As illustrated in
In AMVP mode, an MVP candidate is determined based on the template matching error to pick up the one which reaches the minimum difference between the current block and the reference block templates, and then TM performs only for this particular MVP candidate for MV refinement. TM refines this MVP candidate, starting from full-pel MVD precision (or 4-pel for 4-pel AMVR mode) within a [−8, +8]-pel search range by using iterative diamond search. The AMVP candidate may be further refined by using cross search with full-pel MVD precision (or 4-pel for 4-pel AMVR mode), followed sequentially by half-pel and quarter-pel ones depending on AMVR mode. This search process ensures that the MVP candidate still keeps the same MV precision as indicated by adaptive motion vector resolution (AMVR) mode after TM process.
In the merge mode, similar search method is applied to the merge candidate indicated by the merge index. TM merge may perform all the way down to 1/8-pel MVD precision or skipping those beyond half-pel MVD precision, depending on whether the alternative interpolation filter (that is used when AMVR is of half-pel mode) is used according to merged motion information. Besides, when TM mode is enabled, template matching may work as an independent process or an extra MV refinement process between block-based and subblock-based bilateral matching (BM) methods, depending on whether BM can be enabled or not according to its enabling condition check. When BM and TM are both enabled for a CU, the search process of TM stops at half-pel MVD precision and the resulted MVs are further refined by using the same model-based MVD derivation method as in DMVR.
Inspired by the spatial correlation between reconstructed neighboring pixels and the current coding block, adaptive reorder of merge candidates (ARMC) was proposed to refine the candidates order in a given candidate list. The underlying assumption is that the candidates with less template matching cost have higher probability to be chosen through RDO process, hence should be placed in front positions within the list to reduce the signaling cost.
The reordering method is applied to regular merge mode, template matching (TM) merge mode, and affine merge mode (excluding the SbTMVP candidate). For the TM merge mode, merge candidates are reordered before the refinement process.
After a merge candidate list is constructed, merge candidates are divided into several subgroups. The subgroup size is set to 5. Merge candidates in each subgroup are reordered ascendingly according to cost values based on template matching. For simplification, merge candidates in the last but not the first subgroup are not reordered.
The template matching cost is measured by the sum of absolute differences (SAD) between samples of a template of the current block and their corresponding reference template. The template comprises a set of reconstructed samples neighboring to the current block, while reference template is located by the same motion information of the current block, as illustrated in
For subblock-based merge candidates with subblock size equal to Wsub*Hsub, the above template comprises several sub-templates with the size of Wsub×1, and the left template comprises several sub-templates with the size of 1×Hsub. As shown in
EMCD based on template matching cost reordering has been proposed. Instead of constructing the MVP list based on a predefined traversing order, we investigate an optimized MVP selecting approach by taking advantage of the matching cost in the reconstructed template region, such that more appropriate candidates are included in the list.
It should be noted that the proposed strategy for MVP list construction can be utilized in normal merge and AMVP list construction process and can also be easily extended to other modules that require MVP derivation, e.g., merge with motion vector difference (MMVD), Affine motion compensation, Subblock-based temporal motion vector prediction (SbTMVP) and so on.
1. It is proposed to make use of the TMVP in a non-adjacent area to further improve the effectiveness of the MVP list.
2. The maximum allowed non-adjacent TMVP number in the MVP list may be signaled in the bitstream.
3. The non-adjacent TMVP candidates may locate in the nearest reconstructed frame, but it may also locate in other reconstructed frames.
4. Non-adjacent TMVP candidates may locate in multiple reference pictures.
5. The distances between a non-adjacent area associated with a TMVP candidate and current coding block may be related to the property of the current block.
6. Template represents the reconstructed region that can be used to estimate the priority of an MVP candidate, which may locate in different positions with variable shape.
7. The template may not necessarily locate in the current frame, it may locate in any other reconstructed frame.
8. In one example, a reference template region with the same shape as the template of the current block may be located with an MV, as shown in
9. In one example, the template may not necessarily locate in adjacent area, it may locate in non-adjacent areas that are far away from the current block.
10. In one example, a template may not necessarily contain all the pixels in a certain region, it may contain part of the pixels in a region.
11. In this disclosure, template matching cost associated with a certain MVP candidate serves as a measurement to evaluate the consistency of this candidate and true motion information. Based on this measurement, a more efficient order is generated by sorting the priority of each MVP candidate.
12. All the MVP candidates are sorted in an ascending order regarding the corresponding template matching cost, and the MVP list is constructed by traversing the candidates in the sorted order until the MVP amount reaches the maximum allowed number. In this way, a candidate with a lower matching cost has a higher priority to be included in the ultimate MVP list.
13. It is proposed that the MVP list construction process may involve both reordering of a single group/category and a joint group which contains candidates from more than one category.
14. Multiple groups or categories can be respectively reordered to construct MVP list.
15. The proposed sorting method can also be applied to AMVP mode.
16. The proposed sorting methods may be applied to other coding methods, e.g., for constructing a block vector list of IBC coded blocks.
17. The usage of this method may be controlled with different coding level syntax, including but not limit to one or multiple of PU, CU, CTU, slice, picture, sequence levels.
18. On how to insert sorted candidates to MVP list.
19. The pruning for MVP candidates aims to increase the diversity within the MVP list, which can be realized by using appropriate threshold TH.
20. The pruning threshold can be signaled in the bitstream.
21. The pruning threshold may depend on the characteristics of the current block.
22. The pruning for MVP candidates may be firstly performed within a single or joint group before being sorted.
23. The pruning for MVP candidates may be firstly performed among multiple groups and the sorting may be further applied to one or multiple single/joint groups.
24. After an MVP list with above sorting methods applied, the Adaptive Reordering Merge Candidates (ARMC) process may be further applied.
25. Whether to and/how to enable the sorting process may be dependent on the coding tool.
The template matching based video coding methods is optimized in two aspects. Firstly, reference template derivation process is revised that the interpolation process in the prediction block generation process is replaced by different ways. Secondly, several fast strategies are devised to speedup the tools related to template matching.
It should be noted that the proposed methods can be utilized in ARMC, EMCD and template matching MV refinement, and can also be easily extended to other potential utilizations that require template matching process, e.g., template matching based candidates reorder for merge with motion vector difference (MMVD), Affine motion compensation, Subblock-based temporal motion vector prediction (SbTMVP) and so on. In yet another example, the proposed methods could be applied to other coding tools that requires motion information refinement processes, e.g., bilateral matching-based coding tools.
The detailed embodiments below should be considered as examples to explain general concepts. These embodiments should not be interpreted in a narrow way. Furthermore, these embodiments can be combined in any manner. Combination between this patent application and others are also applicable.
1. It is proposed to replace the interpolation filtering process involved in the motion compensation process of an inter prediction signal generation process by other ways in the reference template generation process.
2. Whether to and/or how to perform EMCD may be based on the maximum allowed candidate number within candidate list and/or available candidate number before being added to a candidate list.
3. It is proposed to organize the available merge candidates into subgroups.
4. It is proposed that a piece of information calculated by a first coding tool utilizing at least one template cost may be reused by a second coding tool utilizing at least one template cost.
An optimized MVP list derivation method based on template matching cost ordering is proposed. Instead of constructing the MVP list based on a predefined traversing order, we investigate an optimized MVP selecting approach by taking advantage of the matching cost in the reconstructed template region, such that more appropriate candidates are included in the list.
It should be noted that the proposed strategy for MVP list construction can be utilized in normal merge and AMVP list construction process and can also be easily extended to other modules that require MVP derivation, e.g., merge with motion vector difference (MMVD), Affine motion compensation, Subblock-based temporal motion vector prediction (SbTMVP) and so on.
In the following discussion, category represents the belongingness of an MVP candidate, e.g., non-adjacent MVP candidates belong to one category; HMVP candidates belonging to another category. A group denotes an MVP candidate set which contains one or multiple MVP candidates. In one example, a single group denotes an MVP candidate set in which all the candidates belong to one category, e.g., adjacent MVP, non-adjacent MVP, HMVP, etc. In another example, a joint group denotes an MVP candidate set which contains candidates from multiple categories.
The detailed embodiments below should be considered as examples to explain general concepts. These embodiments should not be interpreted in a narrow way. Furthermore, these embodiments can be combined in any manner. Combination between this patent application and others are also applicable.
5. Multiple thresholds to determine whether a candidate could be added to a candidate list may be utilized in the candidate pruning process.
6. Multi-pass reordering can be performed to construct an MVP list.
7. At least one virtual candidate (e.g., pairwise MVP and zero MVP) may be involved in the at least one group.
8. The number of candidates of a single/joint group may not be allowed to exceed a maximum candidate number.
9. The construction of a single/joint group may depend on the maximum number constraint Ni.
10. On how to prune MVP candidates.
1) Existing MVP list construction methods target at building a subset with constant MVP number from a given candidate set, which is normally realized by selecting the available candidates in a predefined order. This strategy, however, does not exploit the prior information produced during encoding/decoding process, which may lead to the mismatch between the true motion information and that of the candidates in the constructed MVP list.
2) Existing pruning process for MVP candidate only regards identical MVs as redundancy. Consequently, the constructed MVP list may contain quite similar MVs such that the diversity within the list is limited.
In this disclosure, an enhanced MVP list derivation method based on template matching cost ordering is proposed. Instead of constructing the MVP list based on a predefined traversing order, an optimized MVP selecting approach is investigated by taking advantage of the matching cost in the reconstructed template region, such that more appropriate candidates are included in the list.
It should be noted that the proposed strategy for MVP list construction can be utilized in normal merge and AMVP list construction process and can also be easily extended to other modules that require MVP derivation, e.g., merge with motion vector difference (MMVD), Affine motion compensation, Subblock-based temporal motion vector prediction (SbTMVP) and so on.
In the following discussion, category represents the belongingness of an MVP candidate, e.g., non-adjacent MVP candidates belong to one category; HMVP candidates belonging to another category. A group denotes an MVP candidate set which contains one or multiple MVP candidates. In one example, a single group denotes an MVP candidate set in which all the candidates belong to one category, e.g., adjacent MVP, non-adjacent MVP, HMVP, etc. In another example, a joint group denotes an MVP candidate set which contains candidates from multiple categories.
In the following discussion, “cost” of a candidate may be derived based on template matching or Bilateral matching, with functions such as SAD/SATD/SSD/MR-SAD (mean removal SAD).
The detailed embodiments below should be considered as examples to explain general concepts. These embodiments should not be interpreted in a narrow way. Furthermore, these embodiments can be combined in any manner. Combination between this patent application and others are also applicable.
1. Multiple thresholds may be utilized to determine whether a candidate could be added to a candidate list in the candidate pruning process.
2. On how to construct MVP list.
3. The disclosed methods above can be applied on potential candidates before being put into the candidate list, or may be applied on candidates after being put into the candidate list.
1) Whether to and/or how to apply the disclosed methods above may be signalled at sequence level/group of pictures level/picture level/slice level/tile group level, such as in sequence header/picture header/SPS/VPS/DPS/DCI/PPS/APS/slice header/tile group header.
2) Whether to and/or how to apply the disclosed methods above may be signalled at PB/TB/CB/PU/TU/CU/VPDU/CTU/CTU row/slice/tile/sub-picture/other kinds of region contain more than one sample or pixel.
3) Whether to and/or how to apply the disclosed methods above may be dependent on coded information, such as block size, colour format, single/dual tree partitioning, colour component, slice/picture type.
In one example, when encoder/decoder starts to build an MVP candidate list, multiple small groups will be firstly constructed, where each group comprises the candidates from one or multiple categories. In particular, the number of the candidate in each group should not exceed the maximum allowed number, wherein the maximum number may vary from one group to another. Besides, within-group pruning operation with a constant threshold is conducted along with the construction of each group. After each group is constructed, all or partial of them will further merge into a hybrid group, here the 2nd pass pruning is triggered to exclude the redundant candidates in the larger group. Then, all or partial of the candidates in the mixed group are sorted based on ARMC method, and it should be noted that all or partial candidates before ARMC may be firstly refined by template matching or bilateral matching. Based on the sorted hybrid group, some constructed candidates, i.e., pairwise candidates, may be generated and then insert into the hybrid group along with the 3rd pass pruning operation. And the extended hybrid group performs ARMC again and all the candidates are sorted based on the TM cost. Lastly, if the candidate number in the hybrid group is larger than the maximum allowed value for the MVP list, the final pass pruning operation is conducted. In particular, the template matching cost for all the candidates in the sorted group are calculated, and the minimum cost difference between a candidate and its predecessor among all candidates is determined. If this minimum cost difference is smaller than a constant TH, the candidate will be discarded and it is moved at a further position in the list. This further position is the first position where the cost difference relative to its predecessor is larger than TH. This algorithm stops after a finite number of iterations, or the remaining candidates number reaches the target value for the MVP list.
At block 1110, a plurality of motion vector prediction (MVP) candidates of the current video block is determined. At block 1120, a candidate list of the current video block is determined by applying a plurality of pruning processes to the plurality of MVP candidates. For example, K-pass (K being an integer greater than 1, e.g., K=4) pruning processes may be conducted to construct MVP list. At block 1130, the conversion is performed based on the candidate list.
The method 1100 enables determining the candidate list of the current video block by applying a plurality of pruning processes. It thus can avoid redundant candidate in the candidate list and improve the diversity of the candidate list. In this way, the coding efficiency and coding effectiveness can be improved.
In some embodiments, the plurality of pruning processes comprises a first pass pruning process, and determining the candidate list comprises: determining a group of MVP candidates based on the plurality of MVP candidates; applying the first pass pruning process to the group of MVP candidates; and determining the candidate list based on the pruned group of MVP candidates. For example, the Ist pass pruning (termed as P1) is performed within single or joint group to avoid duplicate candidates.
In some embodiments, the group comprises at least one of: a single group of MVP candidates of a single candidate category, or a joint group of MVP candidates of a plurality of candidate categories.
In some embodiments, the method 1100 further comprises: sorting at least a partial of the pruned group of MVP candidates.
In some embodiments, the sorting is based on an adaptive reordering merge candidates (ARMC) process. For example, partial or all of the groups may sort (i.e., ARMC) after P1.
In some embodiments, the plurality of pruning processes comprises a second pass pruning process, and determining the candidate list comprises: determining a plurality of groups of MVP candidates based on the plurality of MVP candidates; determining at least one hybrid group of MVP candidate based on the plurality of groups; applying the second pass pruning process to the at least one hybrid group of MVP candidates; and determining the candidate list based on the at least one pruned hybrid group of MVP candidates. For example, the 2nd pass pruning (termed as P2) is performed when multiple groups are merged into one or multiple hybrid group(s).
In some embodiments, the method 1100 further comprises: sorting the at least one pruned hybrid group of MVP candidates. Alternatively, in some embodiments, the at least one pruned hybrid group of MVP candidates is not sorted.
In some embodiments, the plurality of pruning processes comprises a third pass pruning process, and determining the candidate list comprises: determining a plurality of groups of MVP candidates based on the plurality of MVP candidates; determining at least one hybrid group of MVP candidates based on the plurality of groups; updating the at least one hybrid group by adding at least one MVP candidate into the at least one hybrid group; applying the third pass pruning process to the at least one hybrid group; and determining the candidate list based on the at least one pruned hybrid group of MVP candidates. For example, some new candidates may be inserted into the hybrid group, and the 3rd pass pruning is triggered to ensure no duplicate exists after the new candidates added.
In some embodiments, the plurality of pruning processes comprises a fourth pass pruning process, and determining the candidate list based on the at least one pruned hybrid group comprises: applying the fourth pass pruning process to the at least one pruned hybrid group; and determining the candidate list based on the at least one pruned hybrid group of MVP candidates. For example, the 4th pass pruning (termed as P4) is performed to further increase the diversity within the hybrid group(s).
In some embodiments, the plurality of pruning processes is utilized separately or in combination. For example, the multiple pass pruning described above may be utilized in a separate or combined way.
In some embodiments, applying the plurality of pruning processes to the plurality of MVP candidates comprises: applying at least a partial of plurality of pruning processes to the plurality of MVP candidates based on an order of the plurality of pruning processes.
In some embodiments, the order of the plurality of pruning processes comprises one of: a first order of a first pass pruning process, a second pass pruning process, and a fourth pass pruning process, a second order of a first pass pruning process, a second pass pruning process, and a third pass pruning process, a third order of a first pass pruning process, and a second pass pruning process, a fourth order of a first pass pruning process, and a third pass pruning process, a fifth order of a first pass pruning process, a third pass pruning process, and a fourth pass pruning process, a sixth order of a first pass pruning process, and a fourth pass pruning process, or a seventh order of a first pass pruning process, a fourth pass pruning process, a second pass pruning process, a third pass pruning process, and a fourth pass pruning process. That is, partial pass is used to construct MVP list, i.e., P1->P2->p4, P1->P2->p3, P1->P2, P1->P3, P1->P3->p4, P1->p4, etc.
In some embodiments, the order of the plurality of pruning processes is changed during the conversion. For example, the order of each pass may change during the construction process, i.e., a later pass pruning may perform before a former pass pruning.
In some embodiments, a first pruning process of the plurality of pruning processes is performed for a plurality of times during the conversion.
In some embodiments, applying the plurality of pruning processes to the plurality of MVP candidates comprises: applying the plurality of pruning processes to the plurality of MVP candidates based on a plurality of thresholds, wherein a threshold of the plurality of thresholds is used to determine whether an MVP candidate of the plurality of MVP candidates is to be added into the candidate list.
In some embodiments, the plurality of thresholds for the plurality of pruning processes is the same or different. For example, the threshold used in different passes may be the same or different.
In some embodiments, a first threshold associated with a pruning process of the plurality of pruning processes is a constant.
In some embodiments, the first threshold is determined from the bitstream. In some embodiments, the method 1100 further comprises: determining the first threshold based on coding information of the current video block.
In some embodiments, the coding information of the current video block comprises at least one of: quantization parameter (QP) of the current video block, or a parameter associated with a rate distortion optimization (RDO) process.
In some embodiments, a plurality of candidate threshold values is stored in a data structure, and the first threshold is determined by: determining an index of the first threshold from the bitstream; and obtaining the first threshold from the data structure based on the index. For example, the data structure may comprise a look up table.
In some embodiments, determining the candidate list by applying a plurality of pruning processes to the plurality of MVP candidates comprises: for a first pruning process of the plurality of pruning processes, determining whether an absolute difference of at least one component of a motion vector (MV) of an MVP candidate of the plurality of MVP candidates and at least one component of a candidate in the candidate list is smaller than a threshold; and in accordance with a determination that the absolute difference is larger than or equal to the threshold, add the MVP candidate into the candidate list.
In some embodiments, the candidate list comprises a motion candidate list. In some embodiments, the motion candidate list comprises at least one of: a merge candidate list, an advanced motion vector prediction (AMVP) candidate list, an extend merge or AMVP list, a sub-block merge candidate list, an affine merge candidate list, a merge with motion vector difference (MMVD) list, a geometric partitioning mode (GPM) list, a template matching merge list, a biliteral matching merge list, an intra block copy (IBC) merge candidate list, an IBC AMVP candidate list, an extend IBC merge or IBC AMVP list, or an IBC-MMVD list.
In some embodiments, a first threshold for a first pruning process of the plurality of pruning processes is different from a second threshold for a second pruning process of the plurality of pruning processes, the first pruning process is applied to a first group of candidates, and the second pruning process is applied to a second group of candidates.
In some embodiments, the first group or the second group comprises at least one of: a single group of MVP candidates of a single candidate category, or a joint group of MVP candidates of a plurality of candidate categories.
In some embodiments, a first threshold for a first pruning process of the plurality of pruning processes is different from a second threshold for a second pruning process of the plurality of pruning processes, the first pruning process is applied to a first subset of candidates of the plurality of MVP candidates, and the second pruning process is applied to a remaining subset of candidates of the plurality of MVP candidates.
In some embodiments, the first subset of candidates comprises a single group of candidates associated with a first candidate category, and a candidate in the remaining subset being associated with a second candidate category different from the first candidate category.
In some embodiments, the first subset comprises adjacent candidates, and the remaining subset comprises at least one of: a non-adjacent MVP candidate, a history-based MVP (HMVP) candidate, a pairwise MVP candidate, or a zero MVP candidate. In some embodiments, the first threshold is larger than or smaller than the second threshold.
In some embodiments, determining the candidate list comprises: determining at least one group of candidates based on the plurality of MVP candidates, a group of candidates comprising MVP candidates associated with at least one candidate category; determining a hybrid group of candidates based on the at least one group; sorting the hybrid group of candidates; updating the sorted hybrid group by adding at least one candidate into the sorted hybrid group; and determining the candidate list by applying a last round pruning to the updated hybrid group of candidates.
In some embodiments, the at least one candidate category comprises at least one of: an adjacent MVP candidate category, a non-adjacent MVP candidate category, a history-based MVP (HMVP) candidate category, a pairwise MVP candidate category, or a constructed MVP candidate category.
In some embodiments, the number of candidates in the at least one group is less than or equal to a threshold number.
In some embodiments, the threshold is a constant or is determined during the conversion. In some embodiments, the threshold number for each of the at least one group is different.
In some embodiments, the at least one group comprises a single group, and determining the single group comprises: adding the plurality of MVP candidates into the single group based on a predefined order of candidate category.
In some embodiments, the number of candidates associated with a candidate category is less than or equal to a threshold number, the threshold number being a constant or being determined during the conversion.
In some embodiments, at least one pruning process is applied to the at least one group of candidates, or at least one pruning process is not applied to the at least one group of candidates.
In some embodiments, the at least one pruning process is performed within the at least one group. In some embodiments, the at least one pruning process is performed among the at least one group.
In some embodiments, at least one pruning threshold for the at least one group is the same or different.
In some embodiments, if the at least one group comprises a single group, the hybrid group is the single group.
In some embodiments, the at least one group comprises a plurality of groups without being applied a first pass pruning process, and determining the hybrid group comprises: applying a second pass pruning process during a merging process for merging the plurality of groups into the hybrid group.
In some embodiments, the at least one group comprises a plurality of groups being applied a first pass pruning process, and determining the hybrid group comprises: merging the plurality of groups into the hybrid group without applying a second pass pruning process.
In some embodiments, the hybrid group of candidates is sorted based on at least one of: adaptive reordering merge candidates (ARMC), or a further metric.
In some embodiments, the method 1100 further comprises: refining at least a partial of the hybrid group based on at least one of: template matching or bilateral matching before or after sorting the hybrid group.
In some embodiments, a zero MVP in the hybrid group is placed at an end of the sorted hybrid group.
In some embodiments, the at least one candidate comprises a constructed candidate.
In some embodiments, the method 1100 further comprises: sorting the updated hybrid group of candidates.
In some embodiments, the constructed candidate is generated based on the sorted hybrid group.
In some embodiments, the constructed candidate comprises a pairwise candidate.
In some embodiments, a pruning process is applied to the updated hybrid group.
In some embodiments, applying a last round pruning to the updated hybrid group of candidates comprises: determining a plurality of template matching costs for candidates in the updated hybrid group of candidates; and selecting a first candidate from the updated hybrid group and determining whether to discard the first candidate by: determining a minimum cost difference between the first candidate in the updated hybrid group and remaining candidates in the updated hybrid group; and in accordance with a determination that the minimum cost difference is smaller than a threshold, discard the first candidate from the updated hybrid group; and selecting a second candidate from the updated hybrid group and determining whether to discard the second candidate.
In some embodiments, the second candidate is in a position where a cost difference relative to a candidate in the MVP candidate list is larger than the threshold. In some embodiments, the selecting the second candidate and determining whether to discard the second candidate is stopped after a predefined number of iterations, or after the number of candidates in the MVP candidate list reaching a predefined number.
In some embodiments, the template matching cost for all the candidates in the sorted list are calculated, and the minimum cost difference between a candidate and its predecessor among all candidates in the list is determined. If this minimum cost difference is smaller than the threshold (TH), the candidate will be discarded and it is moved at a further position in the list. This further position is the first position where the cost difference relative to its predecessor is larger than TH. This algorithm stops after a finite number of iterations, or the remaining candidates number reaches the target value for the MVP list.
In some embodiments, the threshold is determined based on coding information of the current video block. In some embodiments, the coding information of the current video block comprises at least one of: a quantization parameter (QP) of the current video block, or a parameter associated with a rate distortion optimization (RDO) process. For example, the TH may be derived based on the information of current block, i.e., QP or Lagrange multiplier (Lamda) used in RDO process.
In some embodiments, the method is applied to a first candidate before the first candidate being added into the candidate list, or applied to a second candidate after the second candidate being added into the candidate list.
In some embodiments, information regarding applying the method is included in the bitstream.
In some embodiments, the information is included in at least one of: a sequence level, a group of pictures level, a picture level, a slice level, a tile group level, a sequence header. a picture header, a sequence parameter set (SPS), a video parameter set (VPS), a decoded parameter set (DPS), decoding capability information (DCI), a picture parameter set (PPS), an adaptation parameter set (APS), a slice header, or a tile group header.
In some embodiments, the information is included in a region containing more than one sample or pixel.
In some embodiments, the region comprising one of: a prediction block (PB), a transform block (TB), a coding block (CB), a prediction unit (PU), a transform unit (TU), a coding unit (CU), a virtual pipeline data unit (VPDU), a coding tree unit (CTU), a CTU row, a slice, a tile, a subpicture.
In some embodiments, the information is based on coded information of the current video block.
In some embodiments, the coded information comprises at least one of: a coding mode, a block size, a colour format, a single or dual tree partitioning, a colour component, a slice type, or a picture type.
According to further embodiments of the present disclosure, a non-transitory computer-readable recording medium is provided. The non-transitory computer-readable recording medium stores a bitstream of a video which is generated by a method performed by an apparatus for video processing. In the method, a plurality of motion vector prediction (MVP) candidates of a current video block of the video is determined. A candidate list of the current video block is determined by applying a plurality of pruning processes to the plurality of MVP candidates. The bitstream is generated based on the candidate list.
According to still further embodiments of the present disclosure, a method for storing bitstream of a video is provided. In the method, a plurality of motion vector prediction (MVP) candidates of a current video block of the video is determined. A candidate list of the current video block is determined by applying a plurality of pruning processes to the plurality of MVP candidates. The bitstream is generated based on the candidate list. The bitstream is stored in a non-transitory computer-readable recording medium.
Implementations of the present disclosure can be described in view of the following clauses, the features of which can be combined in any reasonable manner.
Clause 1. A method for video processing, comprising: determining, for a conversion between a current video block of a video and a bitstream of the video, a plurality of motion vector prediction (MVP) candidates of the current video block; determining a candidate list of the current video block by applying a plurality of pruning processes to the plurality of MVP candidates; and performing the conversion based on the candidate list.
Clause 2. The method of clause 1, wherein the plurality of pruning processes comprises a first pass pruning process, and determining the candidate list comprises: determining a group of MVP candidates based on the plurality of MVP candidates; applying the first pass pruning process to the group of MVP candidates; and determining the candidate list based on the pruned group of MVP candidates.
Clause 3. The method of clause 2, wherein the group comprises at least one of: a single group of MVP candidates of a single candidate category, or a joint group of MVP candidates of a plurality of candidate categories.
Clause 4. The method of clause 2 or clause 3, further comprising: sorting at least a partial of the pruned group of MVP candidates.
Clause 5. The method of clause 4, wherein the sorting is based on an adaptive reordering merge candidates (ARMC) process.
Clause 6. The method of any of clauses 1-5, wherein the plurality of pruning processes comprises a second pass pruning process, and determining the candidate list comprises: determining a plurality of groups of MVP candidates based on the plurality of MVP candidates; determining at least one hybrid group of MVP candidate based on the plurality of groups; applying the second pass pruning process to the at least one hybrid group of MVP candidates; and determining the candidate list based on the at least one pruned hybrid group of MVP candidates.
Clause 7. The method of clause 6, further comprising: sorting the at least one pruned hybrid group of MVP candidates.
Clause 8. The method of clause 6, wherein the at least one pruned hybrid group of MVP candidates is not sorted.
Clause 9. The method of any of clauses 1-8, wherein the plurality of pruning processes comprises a third pass pruning process, and determining the candidate list comprises: determining a plurality of groups of MVP candidates based on the plurality of MVP candidates; determining at least one hybrid group of MVP candidates based on the plurality of groups; updating the at least one hybrid group by adding at least one MVP candidate into the at least one hybrid group; applying the third pass pruning process to the at least one hybrid group; and determining the candidate list based on the at least one pruned hybrid group of MVP candidates.
Clause 10. The method of clause 9, wherein the plurality of pruning processes comprises a fourth pass pruning process, and determining the candidate list based on the at least one pruned hybrid group comprises: applying the fourth pass pruning process to the at least one pruned hybrid group; and determining the candidate list based on the at least one pruned hybrid group of MVP candidates.
Clause 11. The method of any of clauses 1-10, wherein the plurality of pruning processes is utilized separately or in combination.
Clause 12. The method of any of clauses 1-11, wherein applying the plurality of pruning processes to the plurality of MVP candidates comprises: applying at least a partial of plurality of pruning processes to the plurality of MVP candidates based on an order of the plurality of pruning processes.
Clause 13. The method of clause 12, wherein the order of the plurality of pruning processes comprises one of: a first order of a first pass pruning process, a second pass pruning process, and a fourth pass pruning process, a second order of a first pass pruning process, a second pass pruning process, and a third pass pruning process, a third order of a first pass pruning process, and a second pass pruning process, a fourth order of a first pass pruning process, and a third pass pruning process, a fifth order of a first pass pruning process, a third pass pruning process, and a fourth pass pruning process, a sixth order of a first pass pruning process, and a fourth pass pruning process, or a seventh order of a first pass pruning process, a fourth pass pruning process, a second pass pruning process, a third pass pruning process, and a fourth pass pruning process.
Clause 14. The method of clause 13, wherein the order of the plurality of pruning processes is changed during the conversion.
Clause 15. The method of any of clauses 12-14, wherein a first pruning process of the plurality of pruning processes is performed for a plurality of times during the conversion.
Clause 16. The method of any of clauses 1-11, wherein applying the plurality of pruning processes to the plurality of MVP candidates comprises: applying the plurality of pruning processes to the plurality of MVP candidates based on a plurality of thresholds, wherein a threshold of the plurality of thresholds is used to determine whether an MVP candidate of the plurality of MVP candidates is to be added into the candidate list.
Clause 17. The method of clause 16, wherein the plurality of thresholds for the plurality of pruning processes is the same or different.
Clause 18. The method of clause 16 or clause 17, wherein a first threshold associated with a pruning process of the plurality of pruning processes is a constant.
Clause 19. The method of clause 18, wherein the first threshold is determined from the bitstream.
Clause 20. The method of clause 18 or clause 19, further comprising: determining the first threshold based on coding information of the current video block.
Clause 21. The method of clause 20, wherein the coding information of the current video block comprises at least one of: quantization parameter (QP) of the current video block, or a parameter associated with a rate distortion optimization (RDO) process.
Clause 22. The method of clause 18 or clause 19, wherein a plurality of candidate threshold values is stored in a data structure, and the first threshold is determined by: determining an index of the first threshold from the bitstream; and obtaining the first threshold from the data structure based on the index.
Clause 23. The method of clause 22, wherein the data structure comprises a look up table.
Clause 24. The method of any of clauses 1-23, wherein determining the candidate list by applying a plurality of pruning processes to the plurality of MVP candidates comprises: for a first pruning process of the plurality of pruning processes, determining whether an absolute difference of at least one component of a motion vector (MV) of an MVP candidate of the plurality of MVP candidates and at least one component of a candidate in the candidate list is smaller than a threshold; and in accordance with a determination that the absolute difference is larger than or equal to the threshold, add the MVP candidate into the candidate list.
Clause 25. The method of any of clauses 1-24, wherein the candidate list comprises a motion candidate list.
Clause 26. The method of clause 25, wherein the motion candidate list comprises at least one of: a merge candidate list, an advanced motion vector prediction (AMVP) candidate list, an extend merge or AMVP list, a sub-block merge candidate list, an affine merge candidate list, a merge with motion vector difference (MMVD) list, a geometric partitioning mode (GPM) list, a template matching merge list, a biliteral matching merge list, an intra block copy (IBC) merge candidate list, an IBC AMVP candidate list, an extend IBC merge or IBC AMVP list, or an IBC-MMVD list.
Clause 27. The method of any of clauses 1-26, wherein a first threshold for a first pruning process of the plurality of pruning processes is different from a second threshold for a second pruning process of the plurality of pruning processes, the first pruning process is applied to a first group of candidates, and the second pruning process is applied to a second group of candidates.
Clause 28. The method of clause 27, wherein the first group or the second group comprises at least one of: a single group of MVP candidates of a single candidate category, or a joint group of MVP candidates of a plurality of candidate categories.
Clause 29. The method of any of clauses 1-28, wherein a first threshold for a first pruning process of the plurality of pruning processes is different from a second threshold for a second pruning process of the plurality of pruning processes, the first pruning process is applied to a first subset of candidates of the plurality of MVP candidates, and the second pruning process is applied to a remaining subset of candidates of the plurality of MVP candidates.
Clause 30. The method of clause 29, wherein the first subset of candidates comprises a single group of candidates associated with a first candidate category, and a candidate in the remaining subset being associated with a second candidate category different from the first candidate category.
Clause 31. The method of clause 29 or clause 30, wherein the first subset comprises adjacent candidates, and the remaining subset comprises at least one of: a non-adjacent MVP candidate, a history-based MVP (HMVP) candidate, a pairwise MVP candidate, or a zero MVP candidate.
Clause 32. The method of any of clauses 27-31, wherein the first threshold is larger than or smaller than the second threshold.
Clause 33. The method of any of clauses 1-32, wherein determining the candidate list comprises: determining at least one group of candidates based on the plurality of MVP candidates, a group of candidates comprising MVP candidates associated with at least one candidate category; determining a hybrid group of candidates based on the at least one group; sorting the hybrid group of candidates; updating the sorted hybrid group by adding at least one candidate into the sorted hybrid group; and determining the candidate list by applying a last round pruning to the updated hybrid group of candidates.
Clause 34. The method of clause 33, wherein the at least one candidate category comprises at least one of: an adjacent MVP candidate category, a non-adjacent MVP candidate category, a history-based MVP (HMVP) candidate category, a pairwise MVP candidate category, or a constructed MVP candidate category.
Clause 35. The method of clause 33 or clause 34, wherein the number of candidates in the at least one group is less than or equal to a threshold number.
Clause 36. The method of clause 35, wherein the threshold is a constant or is determined during the conversion.
Clause 37. The method of clause 35, wherein the threshold number for each of the at least one group is different.
Clause 38. The method of any of clauses 33-37, wherein the at least one group comprises a single group, and determining the single group comprises: adding the plurality of MVP candidates into the single group based on a predefined order of candidate category.
Clause 39. The method of clause 38, wherein the number of candidates associated with a candidate category is less than or equal to a threshold number, the threshold number being a constant or being determined during the conversion.
Clause 40. The method of any of clauses 33-39, wherein at least one pruning process is applied to the at least one group of candidates, or at least one pruning process is not applied to the at least one group of candidates.
Clause 41. The method of clause 40, wherein the at least one pruning process is performed within the at least one group.
Clause 42. The method of clause 40, wherein the at least one pruning process is performed among the at least one group.
Clause 43. The method of any of clauses 40-42, wherein at least one pruning threshold for the at least one group is the same or different.
Clause 44. The method of any of clauses 33-43, wherein if the at least one group comprises a single group, the hybrid group is the single group.
Clause 45. The method of any of clauses 33-43, wherein the at least one group comprises a plurality of groups without being applied a first pass pruning process, and determining the hybrid group comprises: applying a second pass pruning process during a merging process for merging the plurality of groups into the hybrid group.
Clause 46. The method of any of clauses 33-43, wherein the at least one group comprises a plurality of groups being applied a first pass pruning process, and determining the hybrid group comprises: merging the plurality of groups into the hybrid group without applying a second pass pruning process.
Clause 47. The method of any of clauses 33-46, wherein the hybrid group of candidates is sorted based on at least one of: adaptive reordering merge candidates (ARMC), or a further metric.
Clause 48. The method of any of clauses 33-47, further comprising: refining at least a partial of the hybrid group based on at least one of: template matching or bilateral matching before or after sorting the hybrid group.
Clause 49. The method of any of clauses 33-48, wherein a zero MVP in the hybrid group is placed at an end of the sorted hybrid group.
Clause 50. The method of any of clauses 33-49, wherein the at least one candidate comprises a constructed candidate.
Clause 51. The method of clause 50, further comprising: sorting the updated hybrid group of candidates.
Clause 52. The method of clause 50 or clause 51, wherein the constructed candidate is generated based on the sorted hybrid group.
Clause 53. The method of any of clauses 50-52, wherein the constructed candidate comprises a pairwise candidate.
Clause 54. The method of any of clauses 50-53, wherein a pruning process is applied to the updated hybrid group.
Clause 55. The method of any of clauses 33-54, wherein applying a last round pruning to the updated hybrid group of candidates comprises: determining a plurality of template matching costs for candidates in the updated hybrid group of candidates; and selecting a first candidate from the updated hybrid group and determining whether to discard the first candidate by: determining a minimum cost difference between the first candidate in the updated hybrid group and remaining candidates in the updated hybrid group; and in accordance with a determination that the minimum cost difference is smaller than a threshold, discard the first candidate from the updated hybrid group; and selecting a second candidate from the updated hybrid group and determining whether to discard the second candidate.
Clause 56. The method of clause 55, wherein the second candidate is in a position where a cost difference relative to a candidate in the MVP candidate list is larger than the threshold.
Clause 57. The method of clause 55 or clause 56, wherein the selecting the second candidate and determining whether to discard the second candidate is stopped after a predefined number of iterations, or after the number of candidates in the MVP candidate list reaching a predefined number.
Clause 58. The method of any of clauses 55-57, wherein the threshold is determined based on coding information of the current video block.
Clause 59. The method of clause 58, wherein the coding information of the current video block comprises at least one of: a quantization parameter (QP) of the current video block, or a parameter associated with a rate distortion optimization (RDO) process.
Clause 60. The method of any of clauses 1-59, wherein the method is applied to a first candidate before the first candidate being added into the candidate list, or applied to a second candidate after the second candidate being added into the candidate list.
Clause 61. The method of any of clauses 1-60, wherein information regarding applying the method is included in the bitstream.
Clause 62. The method of clause 61, wherein the information is included in at least one of: a sequence level, a group of pictures level, a picture level, a slice level, a tile group level, a sequence header. a picture header, a sequence parameter set (SPS), a video parameter set (VPS), a decoded parameter set (DPS), decoding capability information (DCI), a picture parameter set (PPS), an adaptation parameter set (APS), a slice header, or a tile group header.
Clause 63. The method of clause 61, wherein the information is included in a region containing more than one sample or pixel.
Clause 64. The method of clause 63, wherein the region comprising one of: a prediction block (PB), a transform block (TB), a coding block (CB), a prediction unit (PU), a transform unit (TU), a coding unit (CU), a virtual pipeline data unit (VPDU), a coding tree unit (CTU), a CTU row, a slice, a tile, a subpicture.
Clause 65. The method of any of clauses 61-64, wherein the information is based on coded information of the current video block.
Clause 66. The method of clause 65, wherein the coded information comprises at least one of: a coding mode, a block size, a colour format, a single or dual tree partitioning, a colour component, a slice type, or a picture type.
Clause 67. The method of any of clauses 1-66, wherein the conversion includes encoding the current video block into the bitstream.
Clause 68. The method of any of clauses 1-66, wherein the conversion includes decoding the current video block from the bitstream.
Clause 69. An apparatus for video processing comprising a processor and a non-transitory memory with instructions thereon, wherein the instructions upon execution by the processor, cause the processor to perform a method in accordance with any of clauses 1-68.
Clause 70. A non-transitory computer-readable storage medium storing instructions that cause a processor to perform a method in accordance with any of clauses 1-68.
Clause 71. A non-transitory computer-readable recording medium storing a bitstream of a video which is generated by a method performed by an apparatus for video processing, wherein the method comprises: determining a plurality of motion vector prediction (MVP) candidates of a current video block of the video; determining a candidate list of the current video block by applying a plurality of pruning processes to the plurality of MVP candidates; and generating the bitstream based on the candidate list.
Clause 72. A method for storing a bitstream of a video, comprising: determining a plurality of motion vector prediction (MVP) candidates of a current video block of the video; determining a candidate list of the current video block by applying a plurality of pruning processes to the plurality of MVP candidates; generating the bitstream based on the candidate list; and storing the bitstream in a non-transitory computer-readable recording medium.
It would be appreciated that the computing device 1200 shown in
As shown in
In some embodiments, the computing device 1200 may be implemented as any user terminal or server terminal having the computing capability. The server terminal may be a server, a large-scale computing device or the like that is provided by a service provider. The user terminal may for example be any type of mobile terminal, fixed terminal, or portable terminal, including a mobile phone, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal navigation device, personal digital assistant (PDA), audio/video player, digital camera/video camera, positioning device, television receiver, radio broadcast receiver, E-book device, gaming device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof. It would be contemplated that the computing device 1200 can support any type of interface to a user (such as “wearable” circuitry and the like).
The processing unit 1210 may be a physical or virtual processor and can implement various processes based on programs stored in the memory 1220. In a multi-processor system, multiple processing units execute computer executable instructions in parallel so as to improve the parallel processing capability of the computing device 1200. The processing unit 1210 may also be referred to as a central processing unit (CPU), a microprocessor, a controller or a microcontroller.
The computing device 1200 typically includes various computer storage medium. Such medium can be any medium accessible by the computing device 1200, including, but not limited to, volatile and non-volatile medium, or detachable and non-detachable medium. The memory 1220 can be a volatile memory (for example, a register, cache, Random Access Memory (RAM)), a non-volatile memory (such as a Read-Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), or a flash memory), or any combination thereof. The storage unit 1230 may be any detachable or non-detachable medium and may include a machine-readable medium such as a memory, flash memory drive, magnetic disk or another other media, which can be used for storing information and/or data and can be accessed in the computing device 1200.
The computing device 1200 may further include additional detachable/non-detachable, volatile/non-volatile memory medium. Although not shown in
The communication unit 1240 communicates with a further computing device via the communication medium. In addition, the functions of the components in the computing device 1200 can be implemented by a single computing cluster or multiple computing machines that can communicate via communication connections. Therefore, the computing device 1200 can operate in a networked environment using a logical connection with one or more other servers, networked personal computers (PCs) or further general network nodes.
The input device 1250 may be one or more of a variety of input devices, such as a mouse, keyboard, tracking ball, voice-input device, and the like. The output device 1260 may be one or more of a variety of output devices, such as a display, loudspeaker, printer, and the like. By means of the communication unit 1240, the computing device 1200 can further communicate with one or more external devices (not shown) such as the storage devices and display device, with one or more devices enabling the user to interact with the computing device 1200, or any devices (such as a network card, a modem and the like) enabling the computing device 1200 to communicate with one or more other computing devices, if required. Such communication can be performed via input/output (I/O) interfaces (not shown).
In some embodiments, instead of being integrated in a single device, some or all components of the computing device 1200 may also be arranged in cloud computing architecture. In the cloud computing architecture, the components may be provided remotely and work together to implement the functionalities described in the present disclosure. In some embodiments, cloud computing provides computing, software, data access and storage service, which will not require end users to be aware of the physical locations or configurations of the systems or hardware providing these services. In various embodiments, the cloud computing provides the services via a wide area network (such as Internet) using suitable protocols. For example, a cloud computing provider provides applications over the wide area network, which can be accessed through a web browser or any other computing components. The software or components of the cloud computing architecture and corresponding data may be stored on a server at a remote position. The computing resources in the cloud computing environment may be merged or distributed at locations in a remote data center. Cloud computing infrastructures may provide the services through a shared data center, though they behave as a single access point for the users. Therefore, the cloud computing architectures may be used to provide the components and functionalities described herein from a service provider at a remote location. Alternatively, they may be provided from a conventional server or installed directly or otherwise on a client device.
The computing device 1200 may be used to implement video encoding/decoding in embodiments of the present disclosure. The memory 1220 may include one or more video coding modules 1225 having one or more program instructions. These modules are accessible and executable by the processing unit 1210 to perform the functionalities of the various embodiments described herein.
In the example embodiments of performing video encoding, the input device 1250 may receive video data as an input 1270 to be encoded. The video data may be processed, for example, by the video coding module 1225, to generate an encoded bitstream. The encoded bitstream may be provided via the output device 1260 as an output 1280.
In the example embodiments of performing video decoding, the input device 1250 may receive an encoded bitstream as the input 1270. The encoded bitstream may be processed, for example, by the video coding module 1225, to generate decoded video data. The decoded video data may be provided via the output device 1260 as the output 1280.
While this disclosure has been particularly shown and described with references to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present application as defined by the appended claims. Such variations are intended to be covered by the scope of this present application. As such, the foregoing description of embodiments of the present application is not intended to be limiting.
| Number | Date | Country | Kind |
|---|---|---|---|
| PCT/CN2022/123877 | Oct 2022 | WO | international |
This application is a continuation of International Application No. PCT/CN2023/123409, filed on Oct. 8, 2023, which claims the benefit of International Application No. PCT/CN2022/123877 filed on Oct. 8, 2022. The entire contents of these applications are hereby incorporated by reference in their entireties.
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/CN2023/123409 | Oct 2023 | WO |
| Child | 19173577 | US |
