DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks

• Published in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition pp. 8183 - 8192
• Main Authors: Kupyn, Orest, Budzan, Volodymyr, Mykhailych, Mykola, Mishkin, Dmytro, Matas, Jiri
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2018
• Subjects: Convolution; Gallium nitride; Generative adversarial networks; Generators; Image restoration; Kernel; Training
• ISSN: 1063-6919
• DOI: 10.1109/CVPR.2018.00854

We present DeblurGAN, an end-to-end learned method for motion deblurring. The learning is based on a conditional GAN and the content loss. DeblurGAN achieves state-of-the art performance both in the structural similarity measure and visual appearance. The quality of the deblurring model is also eval...