HP
Human Pose and Action Recognition
This cluster of papers focuses on the development and application of deep learning techniques for human action recognition and pose estimation. It covers topics such as spatiotemporal feature learning, convolutional networks, 3D human pose estimation, skeleton-based recognition, and video classification. The research aims to advance the understanding and accurate detection of human actions in various environments.
50,277
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1,003,603
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- Christian Theobalt (238)
- Yi Yang (237)
- Michael J. Black (225)
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- Human Pose and Action Recognition (126,182)
- Video Surveillance and Tracking Methods (31,737)
- Anomaly Detection Techniques and Applications (23,353)
- Hand Gesture Recognition Systems (22,258)
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