research-article

Overview of the H.264/AVC video coding standard

Authors:

T. Wiegand,

G. J. Sullivan,

G. Bjontegaard,

A. LuthraAuthors Info & Claims

IEEE Transactions on Circuits and Systems for Video Technology, Volume 13, Issue 7

Pages 560 - 576

https://doi.org/10.1109/TCSVT.2003.815165

Published: 01 July 2003 Publication History

Abstract

H.264/AVC is newest video coding standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The main goals of the H.264/AVC standardization effort have been enhanced compression performance and provision of a "network-friendly" video representation addressing "conversational" (video telephony) and "nonconversational" (storage, broadcast, or streaming) applications. H.264/AVC has achieved a significant improvement in rate-distortion efficiency relative to existing standards. This article provides an overview of the technical features of H.264/AVC, describes profiles and applications for the standard, and outlines the history of the standardization process.

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Marie ADesnos KMercat AMorin LVanne JZhang L(2024)Advanced fine-tuning procedures to enhance DNN robustness in visual coding for machinesJournal on Image and Video Processing10.1186/s13640-024-00650-32024:1Online publication date: 18-Sep-2024
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Chen BGuo HWu MYang ZYan ZNahrstedt KShu YLiu JTan RHe YChen J(2024)ImmerScope: Multi-view Video Aggregation at Edge towards Immersive Content ServicesProceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems10.1145/3666025.3699324(82-96)Online publication date: 4-Nov-2024
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Xiong FYang JWang R(2024)Enhancing Temporal Context for Learned Video CompressionProceedings of the 2024 9th International Conference on Multimedia and Image Processing10.1145/3665026.3665027(1-5)Online publication date: 20-Apr-2024
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Overview of the H.264/AVC video coding standard
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
  2. Computer graphics
2. General and reference
  1. Cross-computing tools and techniques

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cover image IEEE Transactions on Circuits and Systems for Video Technology

IEEE Transactions on Circuits and Systems for Video Technology Volume 13, Issue 7

July 2003

170 pages

ISSN:1051-8215

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IEEE Press

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Published: 01 July 2003

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Marie ADesnos KMercat AMorin LVanne JZhang L(2024)Advanced fine-tuning procedures to enhance DNN robustness in visual coding for machinesJournal on Image and Video Processing10.1186/s13640-024-00650-32024:1Online publication date: 18-Sep-2024
https://dl.acm.org/doi/10.1186/s13640-024-00650-3
Chen BGuo HWu MYang ZYan ZNahrstedt KShu YLiu JTan RHe YChen J(2024)ImmerScope: Multi-view Video Aggregation at Edge towards Immersive Content ServicesProceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems10.1145/3666025.3699324(82-96)Online publication date: 4-Nov-2024
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Xiong FYang JWang R(2024)Enhancing Temporal Context for Learned Video CompressionProceedings of the 2024 9th International Conference on Multimedia and Image Processing10.1145/3665026.3665027(1-5)Online publication date: 20-Apr-2024
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Zhou FHuang XZhang PWang MWang ZZhou YYin HCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Enhanced Screen Content Image Compression: A Synergistic Approach for Structural Fidelity and Text Integrity PreservationProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681354(7900-7908)Online publication date: 28-Oct-2024
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Guo BBao JChai BWu DHu MCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Lumos: Optimizing Live 360-degree Video Upstreaming via Spatial-Temporal Integrated Neural EnhancementProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681305(7210-7219)Online publication date: 28-Oct-2024
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Wu CQuan GHe GLai XLi YYu WLin XYang CCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)QS-NeRV: Real-Time Quality-Scalable Decoding with Neural Representation for VideosProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3680586(2584-2592)Online publication date: 28-Oct-2024
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Yang JYang CXiong FZhai YWang R(2024)Learned Video Compression with Adaptive Temporal Prior and Decoded Motion-aided Quality EnhancementACM Transactions on Multimedia Computing, Communications, and Applications10.1145/366182420:8(1-21)Online publication date: 13-Jun-2024
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Tang LZhang X(2024)High Efficiency Deep-learning Based Video CompressionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/366131120:8(1-23)Online publication date: 23-Apr-2024
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