5 papers
From Noise to Latent: Generating Gaussian Latents for INR-Based Image Compression
Chaoyi Lin, Yaojun Wu, Yue Li +3
Recent implicit neural representation (INR)-based image compression methods have shown competitive performance by overfitting image-specific latent codes. However, they remain infe…
Neural Video Compression with In-Loop Contextual Filtering and Out-of-Loop Reconstruction Enhancement
Yaojun Wu, Chaoyi Lin, Yiming Wang +4
This paper explores the application of enhancement filtering techniques in neural video compression. Specifically, we categorize these techniques into in-loop contextual filtering…
BiECVC: Gated Diversification of Bidirectional Contexts for Learned Video Compression
Wei Jiang, Junru Li, Kai Zhang +1
Recent forward prediction-based learned video compression (LVC) methods have achieved impressive results, even surpassing VVC reference software VTM under the Low Delay B (LDB) con…
ECVC: Exploiting Non-Local Correlations in Multiple Frames for Contextual Video Compression
Wei Jiang, Junru Li, Kai Zhang +1
In Learned Video Compression (LVC), improving inter prediction, such as enhancing temporal context mining and mitigating accumulated errors, is crucial for boosting rate-distortion…
Releasing the Parameter Latency of Neural Representation for High-Efficiency Video Compression
Gai Zhang, Xinfeng Zhang, Lv Tang +3
For decades, video compression technology has been a prominent research area. Traditional hybrid video compression framework and end-to-end frameworks continue to explore various i…