37 citations · 41 across the 25 of their papers we have counts for
11 papers · 1 filter
Hash Grid Feature Pruning
Yangzhi Ma, Bojun Liu, Jie Li +2
Hash grids are widely used to learn an implicit neural field for Gaussian splatting, serving either as part of the entropy model or for inter-frame prediction. However, due to the…
Real-Time Neural Video Compression with Unified Intra and Inter Coding
Hui Xiang, Yifan Bian, Li Li +3
Neural video compression (NVC) technologies have advanced rapidly in recent years, yielding state-of-the-art schemes such as DCVC-RT that offer superior compression efficiency to H…
In-Loop Filtering Using Learned Look-Up Tables for Video Coding
Zhuoyuan Li, Jiacheng Li, Yao Li +4
In-loop filtering (ILF) is a key technology in video coding standards to reduce artifacts and enhance visual quality. Recently, neural network-based ILF schemes have achieved remar…
EHVC: Efficient Hierarchical Reference and Quality Structure for Neural Video Coding
Junqi Liao, Yaojun Wu, Chaoyi Lin +4
Neural video codecs (NVCs), leveraging the power of end-to-end learning, have demonstrated remarkable coding efficiency improvements over traditional video codecs. Recent research…
Scaling Learned Image Compression Models up to 1 Billion
Yuqi Li, Haotian Zhang, Li Li +2
Recent advances in large language models (LLMs) highlight a strong connection between intelligence and compression. Learned image compression, a fundamental task in modern data com…
Learned Image Compression with Hierarchical Progressive Context Modeling
Yuqi Li, Haotian Zhang, Li Li +1
Context modeling is essential in learned image compression for accurately estimating the distribution of latents. While recent advanced methods have expanded context modeling capac…