mlsanityData to 14 Oct 2026

Cool-chic video: Learned video coding with 800 parameters

arXiv 2402.03179 ↗First posted 5 Feb 2024eess.IV cs.LGcited by 11

Not on the map. Why?

Abstract (arXiv)

We propose a lightweight learned video codec with 900 multiplications per decoded pixel and 800 parameters overall. To the best of our knowledge, this is one of the neural video codecs with the lowest decoding complexity. It is built upon the overfitted image codec Cool-chic and supplements it with an inter coding module to leverage the video's temporal redundancies. The proposed model is able to compress videos using both low-delay and random access configurations and achieves rate-distortion close to AVC while out-performing other overfitted codecs such as FFNeRV. The system is made open-source: orange-opensource.github.io/Cool-Chic.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 8 of its 13 references that are in the map. First posted on arXiv 5 Feb 2024.

Builds on

8 of 13 references.

References · 8

  1. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  2. 2021NeRV: Neural Representations for Videoscited by 256
  3. 2023Neural Video Compression with Diverse Contextscited by 165
  4. 2023HNeRV: A Hybrid Neural Representation for Videoscited by 100
  5. 2023HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representationcited by 71
  6. 2022COOL-CHIC: Coordinate-based Low Complexity Hierarchical Image Codeccited by 51
  7. 2022FFNeRV: Flow-Guided Frame-Wise Neural Representations for Videoscited by 46
  8. 2023Low-complexity Overfitted Neural Image Codeccited by 13

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 2; 2026: 6.

11 papers.