1 citations · 1 across the 5 of their papers we have counts for
5 papers
LSTC-MDA: A Unified Framework for Long-Short Term Temporal Convolution and Mixed Data Augmentation in Skeleton-Based Action Recognition
Feng Ding, Haisheng Fu, Soroush Oraki +1
Skeleton-based action recognition faces two longstanding challenges: the scarcity of labeled training samples and difficulty modeling short- and long-range temporal dependencies. T…
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…
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-…
Enhanced Residual SwinV2 Transformer for Learned Image Compression
Yongqiang Wang, Feng Liang, Haisheng Fu +3
Recently, the deep learning technology has been successfully applied in the field of image compression, leading to superior rate-distortion performance. However, a challenge of man…