Integrating Generative and Contrastive Approaches for Human Action Recognition
This study introduces a novel approach to unsupervised skeleton-based human action recognition by integrating generative and contrastive learning methods. We propose a decomposition of representations, allowing for the preservation of detailed motion information for the generative learning objective...
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| Main Authors: | Pablo Cervantes, Yusuke Sekikawa, Ikuro Sato, Koichi Shinoda |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11020639/ |
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