Task Oriented Video Coding: A Survey
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Abstract (arXiv)
Video coding technology has been continuously improved for higher compression ratio with higher resolution. However, the state-of-the-art video coding standards, such as H.265/HEVC and Versatile Video Coding, are still designed with the assumption the compressed video will be watched by humans. With the tremendous advance and maturation of deep neural networks in solving computer vision tasks, more and more videos are directly analyzed by deep neural networks without humans' involvement. Such a conventional design for video coding standard is not optimal when the compressed video is used by computer vision applications. While the human visual system is consistently sensitive to the content with high contrast, the impact of pixels on computer vision algorithms is driven by specific computer vision tasks. In this paper, we explore and summarize recent progress on computer vision task oriented video coding and emerging video coding standard, Video Coding for Machines.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 28 of its 82 references that are in the map. First posted on arXiv 15 Aug 2022.
Builds on
28 of 82 references.
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16 more
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Citing papers per year: 2023: 2; 2024: 0; 2025: 0; 2026: 1.
3 papers.