BGaitR-Net: an effective neural model for occlusion reconstruction in gait sequences by exploiting the key pose information
Gait recognition in the presence of occlusion is a challenging problem and the solutions proposed to date either lack robustness or depend on several unrealistic constraints. In this work, we propose a Deep Learning framework to detect and reconstruct the occluded frames in a gait sequence. Initiall...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/180136 |