AV1/AVM development at Google

Google is working on a new video codec standard with multiple other industry members within Alliance of Open Media (AOM). Within Google, especially YouTube is actively driving advancements in the AV1 and AVM video codecs to enhance streaming quality and efficiency for diverse video including live and high production value content as well as user-generated content (UGC). Efforts include customizing the AV1 codec for UGC, optimizing quality/bitrate/compute tradeoffs, and developing hardware encoding/decoding support within YouTube's data centers to support AV1 at scale. To accelerate adoption, YouTube works to increase AV1 corpus coverage, expand device compatibility, and contributes to the Alliance for Open Media (AOM) for the ongoing algorithmic improvement of AV1 and AVM and the complexity reduction in both encoder and decoder. To ensure the practical feasibility of AVM, we assess hardware complexity and propose methods to reduce it. YouTube also prioritizes reducing AV1/AVM encoder complexity using approaches like machine learning-based partition search pruning. YouTube led the collective efforts to modify existing tools by chairing HW Subgroup within the AOM group, and developed statistics (bitstream) analysis tools to expedite the development of AVM. Furthermore, YouTube developed a new flow which can enable practical implementation of ML based tools. There are few ML based tools proposed for AVM which includes CNN based loop restoration filter. YouTube's ML implementation flow reduced the complexity of that tool dramatically. This multi-pronged strategy has led to the successful integration of AV1 within Google, and we strive for faster adoption of AVM in the ecosystem.