148 citations · 259 across the 16 of their papers we have counts for
7 papers · 1 filter
Pose-guided Feature Disentangling for Occluded Person Re-identification Based on Transformer
Tao Wang, Hong Liu, Pinhao Song +2
Occluded person re-identification is a challenging task as human body parts could be occluded by some obstacles (e.g. trees, cars, and pedestrians) in certain scenes. Some existing…
Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition
Tianyu Guo, Hong Liu, Zhan Chen +3
In recent years, self-supervised representation learning for skeleton-based action recognition has been developed with the advance of contrastive learning methods. The existing con…
MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation
Wenhao Li, Hong Liu, Hao Tang +2
Estimating 3D human poses from monocular videos is a challenging task due to depth ambiguity and self-occlusion. Most existing works attempt to solve both issues by exploiting spat…
Transformer for Single Image Super-Resolution
Zhisheng Lu, Juncheng Li, Hong Liu +3
Single image super-resolution (SISR) has witnessed great strides with the development of deep learning. However, most existing studies focus on building more complex networks with…
Weakly-supervised 3D Human Pose Estimation with Cross-view U-shaped Graph Convolutional Network
Guoliang Hua, Hong Liu, Wenhao Li +3
Although monocular 3D human pose estimation methods have made significant progress, it is far from being solved due to the inherent depth ambiguity. Instead, exploiting multi-view…
Achieving Domain Generalization in Underwater Object Detection by Domain Mixup and Contrastive Learning
Yang Chen, Pinhao Song, Hong Liu +4
The performance of existing underwater object detection methods degrades seriously when facing domain shift caused by complicated underwater environments. Due to the limitation of…
Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation
Wenhao Li, Hong Liu, Runwei Ding +3
Despite the great progress in 3D human pose estimation from videos, it is still an open problem to take full advantage of a redundant 2D pose sequence to learn representative repre…