LoViF 2026 The First Challenge on Weather Removal in Videos

TL;DR

The LoViF 2026 Challenge aims to advance weather removal in videos by encouraging development of methods that produce visually plausible, temporally consistent restorations, supported by a new dataset and evaluation protocols.

Contribution

Introduction of the first challenge on video weather removal, including a new dataset and evaluation framework to foster progress in realistic video restoration.

Findings

37 participants engaged in the challenge

5 valid final submissions received

Progress in weather removal for videos demonstrated

Abstract

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 this challenge is to advance robust and realistic video restoration under real-world weather conditions, with evaluation protocols that jointly consider fidelity and perceptual quality. The challenge attracted 37 participants and received 5 valid final submissions with corresponding fact sheets, contributing to progress in weather removal for videos. The project is publicly available at https://www.codabench.org/competitions/13462/.