Contributions in this category were discussed XXday XX July XXXX–XXXX (chaired by XXX).
Allocated to BoG (coord by F. Bossen)
JVET-K0390 Rate Control for VVC [Y. . Li, Z. . Chen (Wuhan UniversityUniv.), X. . Li, S. . Liu (Tencent)] [late] JVET-K0472 Crosscheck of JVET-K0390: Rate Control for VVC [Q. . Yu, J. . Zheng (HiSilicon)] [late] JVET-K0206 AHG10: Improved perceptually optimized QP adaptation and associated distortion measure [C. . Helmrich, H. . Schwarz, D. . Marpe, T. . Wiegand (HHI)]
[10]Metrics and evaluation criteria (0)
Contributions in this category were discussed XXday XX July XXXX–XXXX (chaired by XXX).
[12]Plenary meetings, joint Meetings, BoG Reports, and Summary of Actions Taken
12.1Plenary meeting Friday 13 July 1400
The role of the BMS was discussed as follows:
The BMS can be used for holding extra potential features we aren’t so sure about yet
The BMS n eeds to have significant gain over the VTM
The testing in the BMS context sometimes unveils whether gains are independent or have diminished effects when tested with other candidate features.
The BMS can be a common basis for CE tests of modified versions of features
Features that don’t yet have a clear or properly worked out design can be put in the BMS for study.
We need to keep the runnable within some achievable limit on experiment encoding time.
Having a separate tree for (intra) chroma was under consideration; see K0230, CE 1.5.1.1, CE1.5.2.5? This was not in the BMS yet. It was discussed whether to put K0230 in the BMS.
The need for having spec text for any actions taken was emphasized.
WD / VTM
Increasing the upper bound on QP by 12 (no effect on CTC results) (K0251)
PDPC (from K0063). AI 1.0%, RA 0.5%
Intra 67 modes with 6 MPM and truncated binarization of non-MPM modes; otherwise per 3.2.3 (K0368), pending confirmation of mode coding after some experiment result (LGE / Huawei / Qualcomm were to test). AI 1.3%, RA 0.6% Remark: Consider non-normative speed-up
CCLM 1.2%/9.0%/8.0% for Y/Cb/Cr in AI, 0.8%/10%/9.2% for Y/Cb/Cr RA K0190
AMT, both intra and inter, each controlled by an SPS flag, AI 3.3%, RA 2.0%, LB 1.3%). It was suggested to disable inter AMT for CTC (penalty 0.5%, only a non-normative issue - see section 6.6).
6.5% in AI for luma, 3.5% for RA for luma, significantly more for chroma
[Consider increasing QPs of CTC or adding more QPs or spacing them 7 apart] [Further discussed in closing plenary. No action for now.]
BMS
CPR as per HEVC SCC [Consider adding more SCC into CTC Class F and making mandatory, see also K0294 - JB to coordinate]
CTC: 1.3% for AI, 0.5% for RA
Class F: 21% for AI, 16% for RA
SCC TGM 1080p: 54% for AI, 39% for RA
Roughly what that is likely to provide, relative to the prior VTM: 7.8% for AI, 4.0% for RA
3 MPM vs. 6 MPM est. ~0.2% difference for BMS RA, about 0.5% for VTM AI when encoding search is equalized (there is also a difference due to using context modelling in the 6 MPM scheme). Decision: Use 3 MPM for now.
Affine: New prediction & difference coding, fixed 4x4 sub-block, switchable 4/6 parameter model, bug fix affine merge (affine agreed to be moved to VTM in JVET plenary Sunday afternoon)
BMS
BIO with limited WC complexity
DMVR modifications for latency problem solving
Generalized Bipred
Software:
Some speedups e.g. affine
long-term reference mechanism, in combination with pic_output_flag = 0 (non CTC)
Cross-CTU opt. of SAO (non CTC)
Planning of remaining reviews (Tracks A/B) was performed.