31 citations · 53 across the 4 of their papers we have counts for
4 papers
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action Recognition
Zhan Chen, Hong Liu, Tianyu Guo +3
Self-supervised skeleton-based action recognition with contrastive learning has attracted much attention. Recent literature shows that data augmentation and large sets of contrasti…
Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition
Zhan Chen, Sicheng Li, Bing Yang +2
Graph convolutional networks have been widely used for skeleton-based action recognition due to their excellent modeling ability of non-Euclidean data. As the graph convolution is…
Boosting R-CNN: Reweighting R-CNN Samples by RPN's Error for Underwater Object Detection
Pinhao Song, Pengteng Li, Linhui Dai +2
Complicated underwater environments bring new challenges to object detection, such as unbalanced light conditions, low contrast, occlusion, and mimicry of aquatic organisms. Under…
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…