29 citations · 33 across the 4 of their papers we have counts for
5 papers
Data Augmentation for Depression Detection Using Skeleton-Based Gait Information
Jingjing Yang, Haifeng Lu, Chengming Li +2
In recent years, the incidence of depression is rising rapidly worldwide, but large-scale depression screening is still challenging. Gait analysis provides a non-contact, low-cost,…
SM-SGE: A Self-Supervised Multi-Scale Skeleton Graph Encoding Framework for Person Re-Identification
Haocong Rao, Xiping Hu, Jun Cheng +1
Person re-identification via 3D skeletons is an emerging topic with great potential in security-critical applications. Existing methods typically learn body and motion features fro…
Multi-Level Graph Encoding with Structural-Collaborative Relation Learning for Skeleton-Based Person Re-Identification
Haocong Rao, Shihao Xu, Xiping Hu +2
Skeleton-based person re-identification (Re-ID) is an emerging open topic providing great value for safety-critical applications. Existing methods typically extract hand-crafted fe…
Self-Supervised Gait Encoding with Locality-Aware Attention for Person Re-Identification
Haocong Rao, Siqi Wang, Xiping Hu +4
Gait-based person re-identification (Re-ID) is valuable for safety-critical applications, and using only 3D skeleton data to extract discriminative gait features for person Re-ID i…
Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action Recognition
Haocong Rao, Shihao Xu, Xiping Hu +2
Action recognition via 3D skeleton data is an emerging important topic in these years. Most existing methods either extract hand-crafted descriptors or learn action representations…