Search Results for author:
Found 3 papers, 3 papers with code
Quo Vadis, Skeleton Action Recognition ?
To study skeleton-action recognition in the wild, we introduce Skeletics-152, a curated and 3-D pose-annotated subset of RGB videos sourced from Kinetics-700, a large-scale action dataset.
Ranked #1 on
Skeleton Based Action Recognition
on Skeletics-152
NTU-X: An Enhanced Large-scale Dataset for Improving Pose-based Recognition of Subtle Human Actions
The lack of fine-grained joints (facial joints, hand fingers) is a fundamental performance bottleneck for state of the art skeleton action recognition models.
Ranked #1 on
Skeleton Based Action Recognition
on NTU60-X
PSUMNet: Unified Modality Part Streams are All You Need for Efficient Pose-based Action Recognition
At the representation level, we propose a global frame based part stream approach as opposed to conventional modality based streams.
Ranked #13 on
Skeleton Based Action Recognition
on NTU RGB+D 120
