JVET-AN0080 AHG18: CfE response in additional functionality on ultra-low latency and packet loss resilience [S. Ikonin, V. Khamidullin, I. Gribushin, M. Sychev, K. Malyshev, A. Dzugaev, A. Bovsha, X. Ma, E. Alshina (Huawei)]

This contribution describes the coding technology beyond VVC that can be used for ultra-low latency and packet loss resilient decoding scenarios. The described technology re-uses concept of data partitioning of H.263/4, which separates prediction and residual information into different sub-streams. Additionally, entropy coding of residual coefficients is performed using multiple independent entropy coded chunks. A lost aware NN-based filter is further applied to reduce subjective impact of lost residuals and propagation if these errors via inter frame prediction. The evaluation methodology following discussion and contributions of AHG18 is also proposed. According to this methodology the described solution provides average 2.8 dB improvement on top of scalable VTM anchor in broadcast scenario, and freeze rate reduction from 14.7% to 0.4% over single layer VTM anchor in unicast scenario.

NN filter not yet implemented in SADL.

Overhead is counted in NAL units.

It was commented that it might be appropriate to also use channel conditions of other networks.

Data partitioning and entropy coding would need to be normative. NN-based filter might not need to be defined normatively, as it does not change the output in the case of uncorrupted bitstream.

It was commented that a key question would be if all decoders would need to be burdened by tools that are only...

JVET-AO0048 AHG18: Description of the software related to ULL CfE response JVET-AN0080 [V. Khamidullin, K. Malyshev, A. Dzugaev, I. Gribushin, M. Sychev, X. Ma, S. Ikonin, E. Alshina (Huawei)]

This contribution describes the software related to the document JVET-AN0080 “AHG18: CfE response in additional functionality on ultra-low latency and packet loss resilience” presented and evaluated at 40^th JVET meeting. The software contains further modifications on top of previously disclosed in contribution JVET-AN0045. The software is available as branch in AhG18 repository, named ‘jvet-an0080’: https://vcgit.hhi.fraunhofer.de/jvet-ahg-ull/VVCSoftware_VTM/-/tree/jvet-an008. The software implements the coding technology beyond VVC that supports packet loss resilient functionality in ultra-low latency video communication scenario. The technology re-uses concept of data partitioning of H.263/4, which separates prediction and residual information to different sub-streams. Additionally, entropy coding of residual coefficients is performed using multiple independent entropy coded chunks. The error mask is derived based on lost chunks indication, and further propagated following intra- and inter prediction from erroneous blocks. An error cancellation technique including NN-based loss aware filter (LAF), implemented using SADL library, is further applied to reduce subjective impact of reconstruction errors caused by missed residual information. The software was evaluated according to ULL CTC JVET-AN2039. In best preforming configuration with transmission priorities the simulation results...

JVET-AP0200 AHG18: Random Access GOP4 Configuration for Live-streaming Applications evaluated in ULL test conditions [S. Ikonin, I. Gribushin, M. Sychev, K. Malyshev, V. Khamidullin, B. Shevchenko, X. Ma, E. Alshina (Huawei), Z. Deng (Bytedance)]

This contribution reports evaluation results of random access GOP4 configuration suggested by contribution JVET-AM0238 in low latency scenario. Under ULL test conditions described in JVET-AN2039 with latency restriction modified to the range of 70 to 130 ms it was observed that temporal layer 0 is delivered in most of the cases confirming the benefits of temporal scalability in low latency scenario. At the same time temporal layers 1 and 2 are often missed due to network transmission issues leading to instant FPS drop clearly noticeable during video playback. The ULL CfE response published as contribution JVET-AN0080 was also evaluated in the same conditions, and at QP22 demonstrated 2.1 dB of average Y-PSNR improvement, and 28% to 16% of freeze ratio reduction for transmission priority channel, and 0.8 dB average Y-PSNR improvement and 31% to 27% freeze ratio reduction on a channel without transmission priorities, with 1.9% BD-Rate overhead of Y-PSNR. The modifications required for evaluation of RA configuration on top of AHG18 simulation software are also described.

It was agreed to include this as an option for further study into the AHG software.

It was commented that this is not “ultra” low latency, unlike the other scenarios/configurations investigated so far, but a higher variety of cases is probably welcome.