Pseudo Label Association and Prototype-Based Invariant Learning for Semi-Supervised NIR-VIS Face Recognition
Remarkable success of the existing Near-InfraRed and VISible (NIR-VIS) approaches owes to sufficient labeled training data. However, collecting and tagging data from different domains is a time-consuming and expensive task. In this paper, we tackle the NIR-VIS face recognition problem in a semi-supe...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 33(2024) vom: 22., Seite 1448-1463 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Online verfügbar |
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