# Cool-chic video: Learned video coding with 800 parameters

arXiv: https://arxiv.org/abs/2402.03179 · HTML: https://mlsanity.com/paper/2402.03179/

## 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 (most cited first, 8 of 8)

- [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](https://mlsanity.com/paper/2201.05989/) (2022)
- [NeRV: Neural Representations for Videos](https://mlsanity.com/paper/2110.13903/) (2021)
- [Neural Video Compression with Diverse Contexts](https://mlsanity.com/paper/2302.14402/) (2023)
- [HNeRV: A Hybrid Neural Representation for Videos](https://mlsanity.com/paper/2304.02633/) (2023)
- [HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation](https://mlsanity.com/paper/2306.09818/) (2023)
- [COOL-CHIC: Coordinate-based Low Complexity Hierarchical Image Codec](https://mlsanity.com/paper/2212.05458/) (2022)
- [FFNeRV: Flow-Guided Frame-Wise Neural Representations for Videos](https://mlsanity.com/paper/2212.12294/) (2022)
- [Low-complexity Overfitted Neural Image Codec](https://mlsanity.com/paper/2307.12706/) (2023)

## Built on by (most cited first, 11 of 11)

- [NVRC: Neural Video Representation Compression](https://mlsanity.com/paper/2409.07414/) (2024)
- [PNVC: Towards Practical INR-based Video Compression](https://mlsanity.com/paper/2409.00953/) (2024)
- [Good, Cheap, and Fast: Overfitted Image Compression with Wasserstein Distortion](https://mlsanity.com/paper/2412.00505/) (2024)
- [Ultra-lightweight Neural Video Representation Compression](https://mlsanity.com/paper/2512.04019/) (2025)
- [Enhanced Neural Video Representation Compression Across Extreme Complexity and Quality Scales](https://mlsanity.com/paper/2606.28163/) (2026)
- [MLVC: Multi-platform Learned Video Codec for Real-World Deployment](https://mlsanity.com/paper/2606.28027/) (2026)
- [From Noise to Latent: Generating Gaussian Latents for INR-Based Image Compression](https://mlsanity.com/paper/2511.08009/) (2025)
- [Scalable Neural Video Representation Compression](https://mlsanity.com/paper/2609.04273/) (2026)
- [Multi-scale Image Representation Compression](https://mlsanity.com/paper/2609.04274/) (2026)
- [Video Compression with Graph-inspired Neural Representation](https://mlsanity.com/paper/2609.05541/) (2026)
- [Implicit Neural Representation for Hyperspectral Video Compression](https://mlsanity.com/paper/2609.31435/) (2026)

## 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.