Unsupervised Low-Light Video Enhancement With Spatial-Temporal Co-Attention Transformer
Existing low-light video enhancement methods are dominated by Convolution Neural Networks (CNNs) that are trained in a supervised manner. Due to the difficulty of collecting paired dynamic low/normal-light videos in real-world scenes, they are usually trained on synthetic, static, and uniform motion...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 32(2023) vom: 07., Seite 4701-4715
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| 1. Verfasser: |
Lv, Xiaoqian
(VerfasserIn) |
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| Weitere Verfasser: |
Zhang, Shengping,
Wang, Chenyang,
Zhang, Weigang,
Yao, Hongxun,
Huang, Qingming |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article |
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