Human Pose and Action Recognition

Human Pose and Action Recognition is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 29k research works in it since 1969. 9.5% of them reached the world's top 10% most cited for their field and year.

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.

• Action Recognition
• Pose Estimation
• Spatiotemporal Features
• Convolutional Networks
• 3D Human Pose
• Skeleton-Based Recognition
• Video Classification
• Deep Learning
• Human Activity Analysis
• Temporal Convolutional Networks