13 citations · 23 across the 5 of their papers we have counts for
7 papers
MixSTE: Seq2seq Mixed Spatio-Temporal Encoder for 3D Human Pose Estimation in Video
Jinlu Zhang, Zhigang Tu, Jianyu Yang +2
Recent transformer-based solutions have been introduced to estimate 3D human pose from 2D keypoint sequence by considering body joints among all frames globally to learn spatio-tem…
Optical Flow for Video Super-Resolution: A Survey
Zhigang Tu, Hongyan Li, Wei Xie +4
Video super-resolution is currently one of the most active research topics in computer vision as it plays an important role in many visual applications. Generally, video super-reso…
Joint-bone Fusion Graph Convolutional Network for Semi-supervised Skeleton Action Recognition
Zhigang Tu, Jiaxu Zhang, Hongyan Li +2
In recent years, graph convolutional networks (GCNs) play an increasingly critical role in skeleton-based human action recognition. However, most GCN-based methods still have two m…
Model-based 3D Hand Reconstruction via Self-Supervised Learning
Yujin Chen, Zhigang Tu, Di Kang +5
Reconstructing a 3D hand from a single-view RGB image is challenging due to various hand configurations and depth ambiguity. To reliably reconstruct a 3D hand from a monocular imag…
Multi-Attribute Enhancement Network for Person Search
Lequan Chen, Wei Xie, Zhigang Tu +3
Person Search is designed to jointly solve the problems of Person Detection and Person Re-identification (Re-ID), in which the target person will be located in a large number of un…
Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion
Yujin Chen, Zhigang Tu, Di Kang +4
Accurate 3D reconstruction of the hand and object shape from a hand-object image is important for understanding human-object interaction as well as human daily activities. Differen…