1 citations · 1 across the 4 of their papers we have counts for
5 papers
3DM-WeConvene: Learned Image Compression with 3D Multi-Level Wavelet-Domain Convolution and Entropy Model
Haisheng Fu, Jie Liang, Feng Liang +3
Learned image compression (LIC) has recently made significant progress, surpassing traditional methods. However, most LIC approaches operate mainly in the spatial domain and lack m…
WeConvene: Learned Image Compression with Wavelet-Domain Convolution and Entropy Model
Haisheng Fu, Jie Liang, Zhenman Fang +3
Recently learned image compression (LIC) has achieved great progress and even outperformed the traditional approach using DCT or discrete wavelet transform (DWT). However, LIC main…
S2LIC: Learned Image Compression with the SwinV2 Block, Adaptive Channel-wise and Global-inter Attention Context
Yongqiang Wang, Haisheng Fu, Qi Cao +3
Recently, deep learning technology has been successfully applied in the field of image compression, leading to superior rate-distortion performance. It is crucial to design an effe…
Learned Image Compression with Dual-Branch Encoder and Conditional Information Coding
Haisheng Fu, Feng Liang, Jie Liang +3
Recent advancements in deep learning-based image compression are notable. However, prevalent schemes that employ a serial context-adaptive entropy model to enhance rate-distortion…
Fast and High-Performance Learned Image Compression With Improved Checkerboard Context Model, Deformable Residual Module, and Knowledge Distillation
Haisheng Fu, Feng Liang, Jie Liang +3
Deep learning-based image compression has made great progresses recently. However, many leading schemes use serial context-adaptive entropy model to improve the rate-distortion (R-…