NTIRE 2019 Image Dehazing Challenge Report

Codruta O. Ancuti, Cosmin Ancuti, Radu Timofte, Luc Van Gool, Lei Zhang, Ming-Hsuan Yang; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019, pp. 0-0

Abstract


This paper reviews the second challenge on image dehazing (restoration of rich details in hazy image) with focus on proposed solutions and results. The training data consists from 55 hazy images (with dense haze generated in an indoor or outdoor environment) and their corresponding ground truth (haze-free) images of the same scene. The dense haze has been produced using a professional haze/fog generator that imitates the real conditions of haze scenes. The evaluation consists from the comparison of the dehazed images with the ground truth images. The dehazing process was learnable through provided pairs of haze-free and hazy train images. There were 270 registered participants and 23 teams competed in the final testing phase. They gauge the state-of-the-art in image dehazing.

Related Material


[pdf]
[bibtex]
@InProceedings{Ancuti_2019_CVPR_Workshops,
author = {Ancuti, Codruta O. and Ancuti, Cosmin and Timofte, Radu and Van Gool, Luc and Zhang, Lei and Yang, Ming-Hsuan},
title = {NTIRE 2019 Image Dehazing Challenge Report},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}