MS-MH-TCN: Multi-Stage and Multi-Head Temporal Convolutional Network for Action Segmentation

Zengxin Kang; Zhongyi Chu

doi:10.1007/978-981-97-0885-7_5

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MS-MH-TCN: Multi-Stage and Multi-Head Temporal Convolutional Network for Action Segmentation

Zengxin Kang Zhongyi Chu

Year: 2024 Communications in computer and information science Pages: 48-60 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-97-0885-7_5

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Keywords:

Computer science Artificial intelligence Segmentation Action (physics) Stage (stratigraphy) Head (geology) Pattern recognition (psychology) Biology Physics Paleontology

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Human Pose and Action Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Gait Recognition and Analysis

Physical Sciences → Engineering → Biomedical Engineering

MS-MH-TCN: Multi-Stage and Multi-Head Temporal Convolutional Network for Action Segmentation

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