Publications (16)
Learned Video Compression with Feature-level Residuals
Runsen Feng, Yaojun Wu, Zongyu Guo +3
In this paper, we present an end-to-end video compression network for P-frame challenge on CLIC. We focus on deep neural network (DNN) based video compression, and improve the curr…
Conditional Neural Video Coding with Spatial-Temporal Super-Resolution
Henan Wang, Xiaohan Pan, Runsen Feng +2
This document is an expanded version of a one-page abstract originally presented at the 2024 Data Compression Conference. It describes our proposed method for the video track of th…
Exploring the Rate-Distortion-Complexity Optimization in Neural Image Compression
Yixin Gao, Runsen Feng, Zongyu Guo +1
Despite a short history, neural image codecs have been shown to surpass classical image codecs in terms of rate-distortion performance. However, most of them suffer from significan…
UniMIC: Towards Universal Multi-modality Perceptual Image Compression
Yixin Gao, Xin Li, Xiaohan Pan +5
We present UniMIC, a universal multi-modality image compression framework, intending to unify the rate-distortion-perception (RDP) optimization for multiple image codecs simultaneo…
Soft then Hard: Rethinking the Quantization in Neural Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng +1
Quantization is one of the core components in lossy image compression. For neural image compression, end-to-end optimization requires differentiable approximations of quantization,…
Comp-X: On Defining an Interactive Learned Image Compression Paradigm With Expert-driven LLM Agent
Yixin Gao, Xin Li, Xiaohan Pan +7
We present Comp-X, the first intelligently interactive image compression paradigm empowered by the impressive reasoning capability of large language model (LLM) agent. Notably, com…