---
pipeline_tag: image-to-image
---

# LiVeAction: Lightweight, Versatile, and Asymmetric Codec Design for Real-time Operation

LiVeAction is a neural codec architecture designed for real-time operation on resource-constrained devices, such as wearable sensors or remote sensing platforms. It addresses the limitations of generative neural codecs by using an FFT-inspired encoder structure to reduce computational complexity and a variance-based rate penalty to enable efficient training across arbitrary signal modalities.

- **Paper:** [LiVeAction: a Lightweight, Versatile, and Asymmetric Neural Codec Design for Real-time Operation](https://huggingface.co/papers/2605.06628)
- **Project Page:** [https://ut-sysml.github.io/liveaction](https://ut-sysml.github.io/liveaction)
- **Code:** [https://github.com/UT-SysML/liveaction](https://github.com/UT-SysML/liveaction)
- **Library:** [livecodec](https://pypi.org/project/livecodec) (`pip install livecodec`)

## Citation

```bibtex
@inproceedings{jacobellis2026liveaction,
  title={LiVeAction: Lightweight, Versatile, and Asymmetric Codec Design for Real-time Operation},
  author={Jacobellis, Dan and Yadwadkar, Neeraja J.},
  booktitle={IEEE Data Compression Conference (DCC)},
  year={2026},
  url={https://ut-sysml.github.io/liveaction}
}
```