About this video

• Video Title: AV2 Video Codec Architecture
• Channel: Alliance for Open Media
• Speakers: Andrey Norkin
• Duration: 00:25:54

Overview

This video presents the architecture of the AV2 video codec, detailing its advancements over AV1. Andrey Norkin, a research scientist at Netflix and co-chair of the codec working group at the Alliance for Open Media, explains the various tools and features incorporated into AV2, highlighting improvements in compression efficiency, prediction, transforms, quantization, and loop filters. The presentation also touches upon specific use cases like screen content coding and multi-layer video.

Key takeaways

• AV2 Development Status: The AV2 codec development is nearing completion, with low-level tools finalized and specification writing ongoing. A final release is anticipated by the end of the year.
• Performance Improvements: AV2 demonstrates significant gains in compression efficiency, achieving approximately 28.6% PSNR YUV BD-rate savings and 32.6% VMAF bit-rate savings compared to AV1.
• Core Architecture: AV2 maintains a hybrid block-based model but introduces numerous changes and improvements to tools compared to AV1, including larger block sizes (up to 256x256) and recursive partitioning.
• Advanced Prediction Tools: New and enhanced prediction tools include multi-reference line selection, adaptive intra mode coding, weighted prediction, wedge compound modes, temporal interpolated prediction, optical flow refinement, and warp prediction.
• Transform and Quantization Enhancements: AV2 features include improved transforms with matrix multiplications, learned unitary transforms, and secondary transforms. Quantization has been simplified with an exponential function, and quantization matrices are more flexible and efficient to signal.
• Loop Filters and Restoration: Deblocking has been significantly improved with a generalized formula, and new filters like CCSO, CDEF, and guided detail filter are introduced to enhance picture quality.
• Specific Use Cases: AV2 incorporates features for screen content coding, such as palette mode and improved inter-block copy that allows for in-loop filtering. It also supports multi-layer and multi-stream video, including stereo video.

影片介紹

• 影片標題： AV2 影片編碼器架構
• 頻道： Alliance for Open Media
• 講者： Andrey Norkin
• 時長： 00:25:54

概述

這段影片介紹了 AV2 影片編碼器的架構，詳細闡述了它相較於 AV1 的進步之處。Andrey Norkin，Netflix 的研究科學家兼 Alliance for Open Media 編碼工作組的聯合主席，解釋了 AV2 中所包含的各種工具和功能，並強調了在壓縮效率、預測、變換、量化和環內濾鏡等方面的改進。演講中也提到了特定應用場景，例如螢幕內容編碼和多層影片。

主要重點

• AV2 開發狀態： AV2 編碼器的開發已接近完成，底層工具已定稿，規格書編寫工作也正在進行中。預計將在年底前正式發布。
• 效能改進： AV2 在壓縮效率方面取得了顯著的進步，與 AV1 相比，PSNR YUV BD-rate 節省了約 28.6%，VMAF 位元率節省了約 32.6%。
• 核心架構： AV2 沿用了混合區塊式模型，但與 AV1 相比，對工具進行了許多更改和改進，包括更大的區塊尺寸（高達 256x256）和遞迴分割。
• 進階預測工具： 新增和改進的預測工具包括多參考行選擇、自適應畫面內模式編碼、加權預測、楔形複合模式、時間插值預測、光流細化和仿射變換預測。
• 變換與量化增強： AV2 的功能包括改進的變換（使用矩陣乘法）、學習型單元變換和次級變換。量化透過指數函數進行了簡化，量化矩陣的信令更靈活且有效率。
• 環內濾鏡與恢復： 去區塊化（deblocking）得到了顯著改進，採用了通用公式，並引入了 CCSO、CDEF 和 guided detail filter 等新濾鏡來增強畫質。
• 特定應用場景： AV2 整合了用於螢幕內容編碼的功能，例如調色盤模式（palette mode）和改進的區塊間複製（inter-block copy），後者允許進行環內濾鏡處理。它還支援多層和多串流影片，包括立體影片。

關於此影片，您可以問我任何問題

1. 與 AV1 相比，AV2 在位元率節省方面的首要效能提升是什麼？
2. AV2 的分割策略與 AV1 相比有何變化？
3. 您能否描述一下時間插值預測工具及其兩種使用模式？
4. AV2 中去區塊化濾鏡的關鍵改進有哪些？
5. 將此影片內容轉發為一則推文...