DTCM : Joint Optimization of Dark Enhancement and Action Recognition in Videos
Recognizing human actions in dark videos is a useful yet challenging visual task in reality. Existing augmentation-based methods separate action recognition and dark enhancement in a two-stage pipeline, which leads to inconsistently learning of temporal representation for action recognition. To addr...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 32(2023) vom: 17., Seite 3507-3520 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2023
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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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