Search Results for "JVET-L0198"
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Abstract
At the 11th JVET meeting, alternative temporal motion vector prediction(ATMVP) was adopted to VTM-2.0 reference software. In order to reduce both the average and worst-case complexity, this contribution reports the experimental results on three cases of the ATMVP as follows.
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JVET-L0198 CE4-related: Simplification of ATMVP candidate derivation [S. H. Wang, S. S. Wang, S. Ma (Peking University), X. Zheng (DJI)]
PATENTS:
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2025-03-13
US11743485B2
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US20230059008A1
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US12088786B2
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2024-09-10
US20240073417A1
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2024-02-29
WO2021057996A1
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US20230231997A1
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2023-07-20
WO2020244568A1
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2020-12-10
Decisions
JVET-L0198 CE4-related: Simplification of ATMVP candidate derivation [S. H. Wang, S. S. Wang, S. Ma (Peking University), X. Zheng (DJI)]
Citation
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JVET-L0600 Cross-check of JVET-L0198 (CE4-related: Simplification of ATMVP candidate derivation) [X. Xiu (InterDigital)] [late]
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Decisions
JVET-L0600 Cross-check of JVET-L0198 (CE4-related: Simplification of ATMVP candidate derivation) [X. Xiu (InterDigital)] [late]
Citation
Abstract
The main goal of this Core Experiment (CE) is to study removing subjective artifacts at face boundaries, comparing 360° specific coding tools with existing coding tools, such as tiles, combined with non-normative pre- and post-processing. The tested 360° specific coding tools include modifications to in-loop filtering and inter prediction, as well as projection format adaptation. To alleviate seam artifacts, the tested solutions shall modify in-loop filters by either disabling filtering across face discontinuities and/or by using spherical neighbors in the filtering process. The tested solutions will be implemented for the hybrid equi-angular cubemap (HEC) projection and compared to two anchors. The first anchor is the 360° CTC anchor (JVET-L1012), i.e., HEC with padding of 4 samples around face row with blending (PHEC). The second anchor is the CE anchor, which is PHEC with in-loop filters disabled across face discontinuities.
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JVET-L1033 Description of Core Experiment 13 (CE13): Coding tools for 360° omnidirectional video [P. Hanhart, J.-L. Lin, C. Pujara]
This CE was planned to study changes to in-loop filters, inter prediction, post-filtering, projection rotations and packings.
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 or Wednesday of the first week and closing it on the Tuesday or Wednesday of the second week of the SG 16 meeting – a total of 6–7.5 meeting days), and
- Otherwise meeting under ISO/IEC JTC 1/SC 29/WG 11 auspices when it meets (starting meetings on the Wednesday or Thursday prior to such meetings and closing it on the last day of the WG 11 meeting – a total of 8.5 meeting days).
In cases where 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:
- Wed. 9 – Fri. 18 January 2019, 13th meeting under WG 11 auspices in Marrakech, MA.
- Tue. 19 – Wed. 27 March 2019, 14th meeting under ITU-T auspices in Geneva, CH.
- Wed. 3 – Fri. 12 July 2019, 15th meeting under WG 11 auspices in Gothenburg, SE.
- Tue. 1 – Wed. 9 October 2019, 16th meeting under ITU-T auspices in Geneva, CH.
The agreed document deadline for the 13thJVET meeting was planned to be Wednesday 2 January 2019 (a little later than usual due to the proximity of the New Year holiday). Plans for scheduling of agenda items within that meeting...
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Decisions
Jian Qing Zhu (Fujitsu R&D Center)
Citation
Abstract
The BoG on Neural Networks for Video Coding was held on 11 October 2018. The BoG discussed several subjects including: training data set and process, software sharing and simulation, neural network structure and complexity analysis, reporting and comparison procedure, etc. The BoG recommends:
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JVET-L0704 BoG report on Neural Networks for Video Coding [S. Liu, Y. Li]
The BoG on Neural Networks for Video Coding met on 11 October 2018. The BoG discussed several subjects including: training data set and process, software sharing and simulation, neural network structure and complexity analysis, reporting and comparison procedure, etc. The BoG recommended:
To use the Div2K set as the base training set for all proposals;
To establish a software branch for neural network coding tools (proposals);
A template to report neural network structure and complexity;
To consult with hardware experts about practical complexity criteria;
To continue discussing related issues in an ad-hoc group.
The BoG outcome was reviewed Fri 12 Oct 0930 (GJS).
It was noted that the Div2K contains only still images (and only 800 of them). Its use was only encouraged in order to ease comparisons if applicable. Co...
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Decisions
A template had been developed and was attached to the BoG report for use in reporting of results and analysis. Its use in further experiments was encouraged.
adopted
Adopt.Regarding the question of whether we have a PPS or picture header or both.Decision: Use a PPS for now.The picture header topic as a substitute or additional header is for further study.Whether to have some picture header is primarily a coding efficiency issue.Decision: Regarding including some provision for future extensions in the syntax (e.g., multi-layer extension), it was agreed that may do so in cases where this has a very minor impact on the current design
Citation
Abstract not available in document
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JVET-L0691 BoG report on CE4 related contributions [H. Yang]
Reviewed 1500- Monday (GJS)
Three sessions were held, 1600 ~ 2100 on Oct. 5, 0900 ~ 1400 on Oct. 6, and 1400 ~ 2400 on Oct. 7, for discussing 65 technical contributions in six categories,
Affine motion compensation (17)
Line buffer reduction & CPMV unification
Harmonization with other tools, e.g., AMVR, MMVD, merge offset
Miscellaneous
Merge mode enhancement (29)
ATMVP modifications
HMVP modifications
Miscellaneous
Motion vector coding (5)
Weighted prediction (3)
Local illumination compensation (3)
Memory bandwidth reduction (8)
Recommended adoptions to VTM:
Normative changes
Unification of affine CPMV, choose JVET-L0047 method 1 or JVET-L0047 method 2 (the same as JVET-L0373)
Method 1 control point MVs are stored and used only for model inheritance, other places (ATMVP storage, deblocking, motion comp, spatial neighbours for m...
Decisions
Agreed (approx. no coding efficiency impact)
See section 7.4.
Citation
Abstract
This contribution proposes to include the MS-SSIM metric as additional metric in VTM and make MS-SSIM Y mandatory in the CTC for SDR video. A patch for MS-SSIM integrated into VTM 2.0.1 and an updated excel template for the CTC for SDR video are provided. In terms of MS-SSIM Y, VTM2.0.1 achieves -16.28%, -22.86% and -17.47% BD-rate over HM16.18 in AI, RA and LB, respectively. In terms of PSNR Y, the BD-rates over HM16.18 are -18.03%, 23.08% and -18.29% in AI, RA and LB, respectively.
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JVET-L0365 MS-SSIM as an additional metric [Y. Zhao, H. Yang, J. Chen (Huawei), M. Pettersson, R. Sjöberg, P. Wennersten (Ericsson)]
This contribution proposes to include the MS-SSIM metric as additional metric in VTM and make MS-SSIM Y mandatory in the CTC for SDR video. A patch for MS-SSIM integrated into VTM 2.0.1 and an updated excel template for the CTC for SDR video are provided. In terms of MS-SSIM Y, VTM2.0.1 achieves -16.28%, -22.86% and -17.47% BD-rate over HM16.18 in AI, RA and LB, respectively. In terms of PSNR Y, the BD-rates over HM16.18 are -18.03%, 23.08% and -18.29% in AI, RA and LB, respectively.
No test results were provided in the contribution. Some test results, e.g., VTM vs. HM were requested.
A revised version of the contribution contains such results.
For most tools, BD-rate measurements using PSNR or MS-SSIM are very similar.
It was remarked that it may be prefer...
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Decisions
Agreed (approx. no coding efficiency impact)
Citation