AIM 2025 Challenge on Robust Offline Video Super-Resolution: Dataset, Methods and Results

Авторы: Karetin Nikolai, Molodetskikh Ivan, Vatolin Dmitry, Timofte Radu
Сборник: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)
Год издания: 2025
Издательство: IEEE Computer Society
Местоположение издательства: United States
DOI: 10.1109/ICCVW69036.2025.00593
Аннотация: This paper presents the AIM 2025 Challenge on Robust Offline Video Super-Resolution, the first challenge focusing on 4x upscaling of heavily degraded 270p videos to high-quality 1080p sequences. The challenge addresses the practical problem of enhancing low-quality video content while suppressing noise, blur, and compression artifacts under realistic hardware constraints. We introduce a comprehensive benchmark consisting of 30 diverse video clips spanning camera-shot and animated content, along with a novel synthetic degradation pipeline that ensures reproducible results. Our evaluation methodology employs subjective pairwise comparisons conducted through crowdsourcing. The challenge attracted significant participation and established new baselines for robust video super-resolution in challenging real-world scenarios.
Добавил в систему: Москаленко Андрей Викторович

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