KupynOrest/DeblurGAN
Image Deblurring using Generative Adversarial Networks
Implements Conditional Wasserstein GAN with Gradient Penalty combined with VGG-19 perceptual loss for blind motion deblurring in PyTorch. The architecture generalizes to other image-to-image translation tasks (super-resolution, colorization, inpainting, dehazing) and learns residual corrections from paired blurry-sharp image datasets. Pre-trained generator weights are provided for inference on single images.
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