Learning with few labels for skeleton-based action recognition
Human Action Recognition, which involves discerning human actions, is vital for many real-world applications. Skeleton sequences, tracing human body joint trajectories, capture essential human motions, making them appropriate for action recognition. Compared to RGB videos or depth data, 3D skeleton...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/173603 |
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| Institution: | Nanyang Technological University |
| Language: | English |