Search Results for "JVET-M0113"
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Abstract
This contribution proposes modifications to the local QP adjustment signalling aiming at adapting the Quantization Groups (QGs) specification to the specificities of VVC compared to HEVC. More specifically, it is proposed to base QGs on block surface instead of split depth, by using a new inferred control parameter, named subdivision level (subdiv parameter). In addition, to avoid inconsistent QGs detection, a new inferred QG control flag is also introduced. The modifications are expected to result in QGs that are more uniform in size. Corresponding draft text modifications are proposed.
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JVET-M0113 CE7-related: Quantization Group size uniformity [P. de Lagrange, E. François, P. Bordes (Technicolor)]
References:
Decisions
JVET-M0113 CE7-related: Quantization Group size uniformity [P. de Lagrange, E. François, P. Bordes (Technicolor)]
Citation
Abstract
This document reports the work of the JVET ad hoc group on draft text and test model algorithm description editing (AHG2) between the 13th meeting in Marrakech, MA (9-18 January 2019) and the 14th meeting in Geneva, CH, (19-27 March 2019).
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JVET-N0002 JVET AHG report: Draft text and test model algorithm description editing (AHG2) [B. Bross, J. Chen, J. Boyce, S. Kim, S. Liu, Y. Ye]
This document reports the work of the JVET ad hoc group on draft text and test model algorithm description editing (AHG2) between the 13th meeting in Marrakech, MA (9–18 January 2019) and the 14th meeting in Geneva, CH, (19–27 March 2019).
At the 13th JVET meeting, it was decided to include additional coding features for intra picture-prediction, inter-picture prediction, transform, CABAC engine and de-blocking filter in the fourth draft of Versatile Video Coding (VVC D4) and the VVC Test Model 4 (VTM4) encoding. Draft reference software to implement the VVC decoding process and VTM3 encoding method has also been developed.
The normative decoding process for Versatile Video Coding is specified in the VVC draft 4 text specification document. The VVC Test Model 4 (VTM 4) Algorithm and Encoder Description document provides an algorithm description as well as an encoder-side description of the VVC Test Model 4, which serves as a tutorial for the algorithm and encoding model implemented in the VTM4.0 software.
An issue tracker (https://jvet.hhi.fraunhofer.de/trac/vvc) was used to facilitate the reporting of errata with the VVC documents.
References:
JVET-L1001
JVET-L1002
JVET-M0063
JVET-M0064
JVET-M0092
JVET-M0101
JVET-M0102
JVET-M0111
JVET-M0113
JVET-M0118
JVET-M0119
JVET-M0126
JVET-M0128
JVET-M0132
JVET-M0140
JVET-M0142
JVET-M0145
JVET-M0147
JVET-M0160
JVET-M0166
JVET-M0170
JVET-M0171
JVET-M0173
JVET-M0192
JVET-M0193
JVET-M0201
JVET-M0238
JVET-M0246
JVET-M0251
JVET-M0255
JVET-M0257
JVET-M0264
JVET-M0265
JVET-M0273
JVET-M0277
JVET-M0281
JVET-M0297
JVET-M0300
JVET-M0303
JVET-M0328
JVET-M0361
JVET-M0381
JVET-M0407
JVET-M0415
JVET-M0421
JVET-M0427
JVET-M0436
JVET-M0444
JVET-M0446
JVET-M0451
JVET-M0453
JVET-M0464
JVET-M0470
JVET-M0471
JVET-M0479
JVET-M0483
JVET-M0487
JVET-M0497
JVET-M0502
JVET-M0512
JVET-M0685
JVET-M0853
JVET-M0883
JVET-M0908
JVET-M1001
JVET-M1002
JVET-N0189
JVET-N0194
JVET-N0473
Decisions
The AHG recommended to:
Approve the edited JVET-M1001 and JVET-M1002 documents as JVET outputs,
Continue to edit the VVC draft and Test Model documents to ensure that all agreed elements of VVC are fully described,
Compare the VVC documents with the VVC software and resolve any discrepancies that may exist, in collaboration with the software AHG,
Encourage the use of the issue tracker to report issues with the text of both the VVC specification draft and the algorithm and encoder description,
Continue to improve the editorial consistency of VVC WD and Test Model documents,
Ensure that, when considering the addition of new feature to VVC, properly drafted text for addition to the VVC Test Model and/or the VVC Working Draft is made available in a timely manner.
Citation
Abstract
This report summarises the activities of the AhG3 on Test model software development that has taken place between the 13th and 14th JVET meetings.
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JVET-N0003 JVET AHG report: Test model software development (AHG3) [F. Bossen, X. Li, A. Norkin, K. Sührung]
This report summarizes the activities of the AhG3 on test model software development that has taken place between the 13th and 14th JVET meetings.
The software development continued on the GitLab server. VTM version 3.2 was tagged on Jan. 19., VTM 4.0 on Feb. 12. and VTM 4.0.1 on Feb. 26. VTM 4.1 is expected during the 14th JVET meeting.
For core experiments (CEs) the same development workflow was followed as for the last meeting.
VTM software development
Development was continued on the GitLab server, which allows participants to register accounts and use a distributed development workflow based on git.
The server is located at:
https://vcgit.hhi.fraunhofer.de
The registration and development workflow is documented at:
https://vcgit.hhi.fraunhofer.de/jvet/VVCSoftware_VTM/wikis/VVC-Software-Development-Workflow
The VTM software can be found at
https://vcgit.hhi.fraunhofer.de/jvet/VVCSoftware_VTM/
VTM 3.2 was tagged on Jan 19, 2019.
- Changes relate to VTM 3.1 included:
- Removed JVET-Lxxx macros
- Fix for CU results reuse with dual tree (~7% encoder run time reduction for AI)
- Fix for block statistics generation
After one release candidates, VTM 4.0 was tagged on Feb. 12, 2019.
Changes related to VTM 3.2 include:
- JVET-M0453: modified CABAC core engine
- JVET-M0090: change default C[b,r]QpOffsetDualTree to 0, change C[b,r]QpOffset to 1 for CTC
- JVET-M0421: Split-first signalling for partitioning
- JVET-M0464: UniMTS
- JVET-M0479: 18-bit Mv clip
- JVET-M0502: context for prediction mode flag
- J...
References:
JVET-L0686
JVET-M0055
JVET-M0063
JVET-M0064
JVET-M0068
JVET-M0090
JVET-M0091
JVET-M0101
JVET-M0102
JVET-M0111
JVET-M0113
JVET-M0116
JVET-M0117
JVET-M0118
JVET-M0119
JVET-M0126
JVET-M0132
JVET-M0140
JVET-M0142
JVET-M0145
JVET-M0147
JVET-M0170
JVET-M0173
JVET-M0192
JVET-M0193
JVET-M0204
JVET-M0228
JVET-M0238
JVET-M0240
JVET-M0246
JVET-M0247
JVET-M0253
JVET-M0255
JVET-M0257
JVET-M0264
JVET-M0265
JVET-M0273
JVET-M0277
JVET-M0281
JVET-M0297
JVET-M0303
JVET-M0312
JVET-M0328
JVET-M0338
JVET-M0381
JVET-M0407
JVET-M0409
JVET-M0415
JVET-M0421
JVET-M0427
JVET-M0428
JVET-M0436
JVET-M0444
JVET-M0446
JVET-M0451
JVET-M0453
JVET-M0464
JVET-M0466
JVET-M0470
JVET-M0471
JVET-M0479
JVET-M0483
JVET-M0487
JVET-M0497
JVET-M0502
JVET-M0512
JVET-M0600
JVET-M0685
JVET-M0823
JVET-M0839
JVET-M0853
JVET-M0854
JVET-M0864
JVET-M0883
JVET-M0908
JVET-N0446
JVET-N0503
._HM-16.20_vs_VTM-4.0.xlsm
._JVET-N0003-v1.docx
._VTM-3.0_vs_VTM-4.0.xlsm
._VTM-3.0_vs_VTM-4.0_oldCTC.xlsm
._VTM-3.2_vs_VTM-4.0.xlsm
._VTM-3.2_vs_VTM-4.0_oldCTC.xlsm
._VTM-4.0_vs_VTM-4.0-parsets.xlsm
._VTM-4.0_vs_VTM-4.0.1.xlsm
HM-16.20_vs_VTM-4.0.xlsm
JVET-N0003-v1.docx
VTM-3.0_vs_VTM-4.0.xlsm
VTM-3.0_vs_VTM-4.0_oldCTC.xlsm
VTM-3.2_vs_VTM-4.0.xlsm
VTM-3.2_vs_VTM-4.0_oldCTC.xlsm
VTM-4.0_vs_VTM-4.0-parsets.xlsm
VTM-4.0_vs_VTM-4.0.1.xlsm
Decisions
Review and approve updated guidelines for reference software development
Citation
Abstract
The purpose of this Core Experiment (CE) is to investigate the coding tools related to neural network (NN) based loop filter on top of the Test Model. In this CE, the impact of the position of the NN based filter in the filter chain, the benefit of the CTU level NN filter adaptive on/off switching, and the generalization capability when QP is different from the training QP will be investigated. In addition to the encoder and decoder run-times, the network information, e.g., network parameter numbers, number of layers, and convolution kernel size will also be evaluated. The list of tools and experiments to be performed are detailed in this document.
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JVET-M1033 Description of Core Experiment 13 (CE13): Neural-network based loop filtering [Y. Li, S. Liu, K. Kawamura]
Future meeting plans, expressions of thanks, and closing of the meeting
Future meeting plans were established according to the following guidelines:
Meeting under ITU-T SG 16 auspices when it meets (starting meetings on the Tuesday of the first week and closing it on the Wednesday of the second week of the SG 16 meeting – a total of 9 meeting days), and
Otherwise meeting under ISO/IEC JTC 1/SC 29/WG 11 auspices when it meets (starting meetings on the Wednesday prior to such meetings and closing it at lunchtime on the last day of the WG 11 meeting – a total of 9.5 meeting days).
In cases where an exceptionally high workload is expected for a meeting, an earlier starting date may be defined.
Some specific future meeting plans (to be confirmed) were established as follows:
T...
Decisions
Jian Qing Zhu (Fujitsu R&D Center)
Citation
Abstract
This contribution provides the report of the BoG on neural networks (NN) for video coding, especially for neural network based loop filter. An information report (JVET-M0691) is discussed in this BoG, and then the CE plan.
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JVET-M0904 BoG report on neural networks for video coding [Y. Li, S. Liu]
This BoG report was presented in Track B on Thursday 17 January 1500-1815 (chaired by JRO).
This contribution provides the report of the BoG on neural networks (NN) for video coding, especially for neural network-based loop filtering. An information report (JVET-M0691) was discussed in this BoG, and then a CE plan.
The BoG recommended the following plan of a CE:
Divide the 6 NN based loop filter methods into two categories and build two sub CE tests.
SubCE1 is the test for sequence-adaptive (two-pass) method, SubCE2 is the test for sequence-independent (one-pass) method.
Investigate the impact of NN filter position in the filter chain.
Due to there being many test cases, only choose some cases to test, as defined below.
For SubCE1:
anchor: DBF + SAO + ALF
case 1a: DBF + SAO + ALF + NN filter, which is the case curr...
Decisions
For the resulting CE plan, see JVET-M1033.
adopted
all the suggested adoptions are confirmed by trackB
Citation
Abstract not available in document
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JVET-M0901 BoG report on quantization control related contributions [Y. Ye]
This report was reviewed in Track A on Monday 16 January 1645–1800 (chaired by GJS).
There were 8 technical contributions in the quantization control category.
The first BoG session was held 2000–2330 on 15 Janurary 2019 in Olympia. The second BoG session was held 1300–1510 on 16 January 2019 in Saba.
Section 1 of the document summarizes the BoG’s recommendations. Section 2 of the document contains detailed notes on the BoG discussions. The following aspects were discussed in the track review:
JVET-M0188 (On quantization parameter signalling considering CU area) and JVET-M0113 (CE7-related: Quantization Group size uniformity)
These two proposals solved the same problem of incoherent quantization group (QG) definition in VVC draft 3. They proposed essentially the same solution. However, the two proposals had diffe...
Decisions
Initialize QP from the bottom left CU of the above CTU row when decoding the first CU of a CTU on the left edge of a tile (text was provided in a revision of JVET-M0685)
See section 6.15.
Citation
Abstract
This contribution proposes two modifications related to transform type signalling and residual coding for transform skip. The first modification includes aligning the cases in which transform skip (TS) and multiple transform selection (MTS) apply. This limits TS to luma transform blocks as well as extends it to transform block sizes up to 32x32. The second modification constitutes of a modified transform coefficient level coding for the TS residual. Relative to the regular residual coding case, the residual coding for TS includes no signalling of the last x/y position, coded_sub_block_flag coded for every subblock, sig_coeff_flag context modelling with reduced template, a single context model for abs_level_gt1_flag and par_level_flag, context modeling for the sign flag, additional greater than 5, 7, 9 flags, modified Rice parameter derivation for the remainder binarization and a limit for the number of context coded bins per sample. The proposed joint signalling (first modification) provides on average (BD-rate Y, enc. time, dec.time):
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JVET-M0464 Non-CE8: Unified Transform Type Signalling and Residual Coding for Transform Skip [B. Bross, T. Nguyen, P. Keydel, H. Schwarz, D. Marpe, T. Wiegand (HHI)]
This contribution proposes two modifications related to transform type signalling and residual coding for transform skip. The first modification includes aligning the cases in which transform skip (TS) and multiple transform selection (MTS) apply. This limits TS to luma transform blocks as well as extends it to transform block sizes up to 32x32. The second modification constitutes of a modified transform coefficient level coding for the TS residual. Relative to the regular residual coding case, the residual coding for TS includes no signalling of the last x/y position, coded_sub_block_flag coded for every subblock, sig_coeff_flag context modelling with reduced template, a single context model for abs_level_gt1_flag and par_l...
References:
._JVET-M0464-TS32Y_CPR0.xlsm
._JVET-M0464-uniMTS-DraftText_r1.docx
._JVET-M0464-uniMTS-Nt2_CPR0.xlsm
._JVET-M0464-uniMTS-Nt3_CPR0.xlsm
._JVET-M0464-uniMTS-Nt3_CPR1.xlsm
._JVET-M0464-uniMTS-Nt3_TSRC_CCB2_CPR0.xlsm
._JVET-M0464-uniMTS-Nt3_TSRC_CCB3_CPR0.xlsm
._JVET-M0464-uniMTS-Nt3_TSRC_CCB3_CPR0_r1.xlsm
._JVET-M0464-uniMTS-Nt3_TSRC_CCB8_CPR0.xlsm
._JVET-M0464-uniMTS-Nt3_TSRC_CCB8_CPR1.xlsm
._JVET-M0464-uniMTS-Nt4_CPR0.xlsm
._JVET-M0464-uniMTS-Nt5_CPR0.xlsm
._JVET-M0464-v4.docx
._JVET-M0464_r1.pdf
JVET-M0464-TS32Y_CPR0.xlsm
JVET-M0464-uniMTS-DraftText_r1.docx
JVET-M0464-uniMTS-Nt2_CPR0.xlsm
JVET-M0464-uniMTS-Nt3_CPR0.xlsm
JVET-M0464-uniMTS-Nt3_CPR1.xlsm
JVET-M0464-uniMTS-Nt3_TSRC_CCB2_CPR0.xlsm
JVET-M0464-uniMTS-Nt3_TSRC_CCB3_CPR0.xlsm
JVET-M0464-uniMTS-Nt3_TSRC_CCB3_CPR0_r1.xlsm
JVET-M0464-uniMTS-Nt3_TSRC_CCB8_CPR0.xlsm
JVET-M0464-uniMTS-Nt3_TSRC_CCB8_CPR1.xlsm
JVET-M0464-uniMTS-Nt4_CPR0.xlsm
JVET-M0464-uniMTS-Nt5_CPR0.xlsm
JVET-M0464-v4.docx
JVET-M0464_r1.pdf
Decisions
adopted
Later, results with a CPR-on anchor were reported. It was demonstrated that large-block TS still provides a benefit for screen content (1.6%, 4.9% for F/TGM in AI, 1.7%, 5.9% for LD). The adoption is reported elsewhere (from Track A).
adopted
Adopt (modified as noted)
Citation