Rain to Rain: Learning Real Rain Removal Without Ground Truth
Image deraining is a low-level restoration task that has become quite popular during the past decades. Although recent data-driven deraining models exhibit promising results, most of these models are trained on synthetic rain data sets which do not generalize well when applied to real rain images. W...
| 主要な著者: | , , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
IEEE
2021-01-01
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| シリーズ: | IEEE Access |
| 主題: | |
| オンライン･アクセス: | https://ieeexplore.ieee.org/document/9400826/ |