NEVC is a neural video coding framework designed for highly efficient video compression. By integrating cutting-edge neural network models, NEVC pushes the boundaries of encoding performance and efficiency.
This repository provides access to code, pretrained models, and research papers for various versions of NEVC.
Release Notes
NEVC-1.0 - First Release
Release Date: Sep 5th, 2025
Key Features:
This version implements the core concepts and methods from the paper “EHVC: Efficient Hierarchical Reference and Quality Structure for Neural Video Coding”, accepted at ACM MM 2025.
📝 Codec Versions Overview
The following table provides details on different versions of the NEVC codec, along with associated papers, code, and checkpoints.
Develop a neural-based video codec that offers efficient video compression.
Achieve major enhancements in encoding performance and compression efficiency.
Citation
If you find NEVC or any part of this repository helpful in your research or projects, we kindly ask you to consider citing the following papers:
EHVC: Efficient Hierarchical Reference and Quality Structure for Neural Video Coding Junqi Liao, Yaojun Wu, Chaoyi Lin, Zhipin Deng, Li Li, Dong Liu, Xiaoyan Sun, ACM MM 2025. ```bibtex
@inproceedings{liao2025ehvc,
title={EHVC: Efficient Hierarchical Reference and Quality Structure for Neural Video Coding},
author={Liao, Junqi and Wu, Yaojun and Lin, Chaoyi and Deng, Zhipin and Li, Li and Liu, Dong and Sun, Xiaoyan},
booktitle={Proceedings of the 33rd ACM International Conference on Multimedia},
year={2025}
}
License
NEVC is licensed under the BSD 3-Clause Clear License
NEVC - Neural Efficient Video Coding
NEVC is a neural video coding framework designed for highly efficient video compression. By integrating cutting-edge neural network models, NEVC pushes the boundaries of encoding performance and efficiency.
This repository provides access to code, pretrained models, and research papers for various versions of NEVC.
NEVC-1.0 - First Release
📝 Codec Versions Overview
The following table provides details on different versions of the NEVC codec, along with associated papers, code, and checkpoints.
If you find NEVC or any part of this repository helpful in your research or projects, we kindly ask you to consider citing the following papers:
Junqi Liao, Yaojun Wu, Chaoyi Lin, Zhipin Deng, Li Li, Dong Liu, Xiaoyan Sun, ACM MM 2025.
```bibtex @inproceedings{liao2025ehvc, title={EHVC: Efficient Hierarchical Reference and Quality Structure for Neural Video Coding}, author={Liao, Junqi and Wu, Yaojun and Lin, Chaoyi and Deng, Zhipin and Li, Li and Liu, Dong and Sun, Xiaoyan}, booktitle={Proceedings of the 33rd ACM International Conference on Multimedia}, year={2025} }
NEVC is licensed under the BSD 3-Clause Clear License