SSRT: A Sequential Skeleton RGB Transformer to Recognize Fine-Grained Human-Object Interactions and Action Recognition
Author:
Affiliation:
1. Department of Integrated System Engineering, School of Global Convergence Studies, Inha University, Incheon, South Korea
2. Department of Information and Communication Engineering, Inha University, Incheon, South Korea
Funder
Inha University’s Research Grant
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10130506.pdf?arnumber=10130506
Reference57 articles.
1. Skeleton Sequence and RGB Frame Based Multi-Modality Feature Fusion Network for Action Recognition
2. A Review on Explainability in Multimodal Deep Neural Nets
3. Fusion of Skeleton and RGB Features for RGB-D Human Action Recognition
4. Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition
5. VPN: Learning Video-Pose Embedding for Activities of Daily Living
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