Weakly supervised coarse-to-fine learning for human action segmentation in HCI videos

Longshuai Sheng; Ce Li

doi:10.1007/s11042-022-13792-1

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Weakly supervised coarse-to-fine learning for human action segmentation in HCI videos

Longshuai Sheng Ce Li

Year: 2022 Journal: Multimedia Tools and Applications Vol: 82 (9)Pages: 12977-12993 Publisher: Springer Science+Business Media

DOI: 10.1007/s11042-022-13792-1

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Keywords:

Computer science Segmentation Artificial intelligence Annotation Frame (networking) Pattern recognition (psychology) Task (project management) Partition (number theory) Cut Machine learning Image segmentation Mathematics

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Human Pose and Action Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Video Surveillance and Tracking Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Multimodal Machine Learning Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Weakly supervised coarse-to-fine learning for human action segmentation in HCI videos

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