29 citations · 57 across the 5 of their papers we have counts for
5 papers
MLIC++: Linear Complexity Multi-Reference Entropy Modeling for Learned Image Compression
Wei Jiang, Jiayu Yang, Yongqi Zhai +2
The latent representation in learned image compression encompasses channel-wise, local spatial, and global spatial correlations, which are essential for the entropy model to captur…
HFLIC: Human Friendly Perceptual Learned Image Compression with Reinforced Transform
Peirong Ning, Wei Jiang, Ronggang Wang
In recent years, there has been rapid development in learned image compression techniques that prioritize ratedistortion-perceptual compression, preserving fine details even at low…
LLIC: Large Receptive Field Transform Coding with Adaptive Weights for Learned Image Compression
Wei Jiang, Peirong Ning, Jiayu Yang +3
The effective receptive field (ERF) plays an important role in transform coding, which determines how much redundancy can be removed during transform and how many spatial priors ca…
Butterfly: Multiple Reference Frames Feature Propagation Mechanism for Neural Video Compression
Feng Wang, Haihang Ruan, Fei Xiong +3
Using more reference frames can significantly improve the compression efficiency in neural video compression. However, in low-latency scenarios, most existing neural video compress…
Rethinking Depth Estimation for Multi-View Stereo: A Unified Representation
Rui Peng, Rongjie Wang, Zhenyu Wang +2
Depth estimation is solved as a regression or classification problem in existing learning-based multi-view stereo methods. Although these two representations have recently demonstr…