Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label Diffusion
Understanding foggy image sequence in driving scene is critical for autonomous driving, but it remains a challenging task due to the difficulty in collecting and annotating real-world images of adverse weather. Recently, self-training strategy has been considered as a powerful solution for unsupervi...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 31(2022) vom: 09., Seite 3525-3540
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| 1. Verfasser: |
Liao, Liang
(VerfasserIn) |
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| Weitere Verfasser: |
Chen, Wenyi,
Xiao, Jing,
Wang, Zheng,
Lin, Chia-Wen,
Satoh, Shin'ichi |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2022
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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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