LoViF 2026 The First Challenge on Weather Removal in Videos
This paper presents a review of the LoViF 2026 Challenge on Weather Removal in Videos. The challenge encourages the development of methods for restoring clean videos from inputs degraded by adverse weather conditions such as rain and snow, with an emphasis on achieving visually plausible and temporally consistent results while preserving scene structure and motion dynamics. To support this task, we introduce a new short-form WRV dataset tailored for video weather removal. It consists of 18 videos 1,216 synthesized frames paired with 1,216 real-world ground-truth frames at a resolution of 832 x 480, and is split into training, validation, and test sets with a ratio of 1:1:1. The goal of th...
| Authors | Chenghao Qian, Xin Li, Yeying Jin et al. |
|---|---|
| Primary category | cs.CV |
| Published | 12 April 2026 |
| Last updated at source | 14 April 2026 |
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