[ICCV 2019] "DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better" by Orest Kupyn, Tetiana Martyniuk, Junru Wu, Zhangyang Wang
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Updated
Jul 14, 2022 - Python
[ICCV 2019] "DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better" by Orest Kupyn, Tetiana Martyniuk, Junru Wu, Zhangyang Wang
Tensorflow implementation of DeblurGAN(Blind Motion Deblurring Using Conditional Adversarial Networks)
Unofficial tensorflow (tf) implementation of DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks
This is a lightweight GAN developed for real-time deblurring. The model has a super tiny size and a rapid inference time. The motivation is to boost marker detection in robotic applications, however, you may use it for other applications definitely.
Using deblur GAN on custom dataset
This is a very simplified ipynb code for KupynOrest's Deblur GAN code. DeblurGAN addresses the challenge of end-to-end image deblurring through the use of conditional Generative Adversarial Networks (cGANs).I have used pytorch for this implementation.
Image Deblurring using Generative Adversarial Networks
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