AV1/AVM development at Google

In Suk Chong; Joe Young; Shan Li; Conor McCullough; Stan Vitvitskyy; Ville-Mikko Rautio

doi:10.1117/12.3031747

30 September 2024 AV1/AVM development at Google

In Suk Chong, Joe Young, Shan Li, Conor McCullough, Stan Vitvitskyy, Ville-Mikko Rautio

Proceedings Volume 13137, Applications of Digital Image Processing XLVII; 131370V (2024) https://doi.org/10.1117/12.3031747
Event: Optical Engineering + Applications, 2024, San Diego, California, United States

Abstract

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.

Conference Presentation

Citation Download Citation

In Suk Chong, Joe Young, Shan Li, Conor McCullough, Stan Vitvitskyy, and Ville-Mikko Rautio "AV1/AVM development at Google", Proc. SPIE 13137, Applications of Digital Image Processing XLVII, 131370V (30 September 2024); https://doi.org/10.1117/12.3031747

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available