About
Contact & Profiles
A5101694974
Research Areas
- Human Pose and Action Recognition
- Multimodal Machine Learning Applications
- Gait Recognition and Analysis
- Video Analysis and Summarization
- Hand Gesture Recognition Systems
Ritsumeikan University
2023-2024
Graph Convolutional Networks (GCNs) have gained widespread adoption in modeling human skeleton sequences for two-person interaction recognition. Most GCN-based models achieve state-of-the-art results by leveraging either intra-body or inter-body connections. However, using only relations may ignore important interactive features between two individuals, whereas relying on weaken the specific motion dynamics of each skeleton. To address these shortcomings, we propose a Distinct...
10.1109/access.2023.3309420
article
EN
cc-by-nc-nd
IEEE Access
2023-01-01
10.1109/iccre61448.2024.10589823
article
EN
2024-05-10
Coming Soon ...