GT-Rain Single Image Deraining Challenge Report
원문 초록
This report reviews the results of the GT-Rain challenge on single image deraining at the UG2+ workshop at CVPR 2023. The aim of this competition is to study the rainy weather phenomenon in real world scenarios, provide a novel real world rainy image dataset, and to spark innovative ideas that will further the development of single image deraining methods on real images. Submissions were trained on the GT-Rain dataset and evaluated on an extension of the dataset consisting of 15 additional scenes. Scenes in GT-Rain are comprised of real rainy image and ground truth image captured moments after the rain had stopped. 275 participants were registered in the challenge and 55 competed in the final testing phase.
함께 살펴볼 논문
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Iterative Optimal Attention and Local Model for Single Image Rain Streak Removal
A Hybrid Transformer-Mamba Network for Single Image Deraining
Explore Internal and External Similarity for Single Image Deraining with Graph Neural Networks
Exploiting Regional Information Transformer for Single Image Deraining
Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge
Controlling Vision-Language Models for Multi-Task Image Restoration
토론
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