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Single Image Super Resolution Dataset And Study
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Generative Adversarial Networks arXiv:1809.00219v2 [cs.CV ...
arxiv.orgAbstract. The Super-Resolution Generative Adversarial Network (SR-GAN) [1] is a seminal work that is capable of generating realistic textures during single image super-resolution. However, the hallucinated details are often accompanied with unpleasant artifacts. To further enhance the visual quality, we thoroughly study three key components of ...
Deep Image Prior - CVF Open Access
openaccess.thecvf.comcommon paradigm of training a ConvNet on a large dataset of example images, we fit a generator network to a single degraded image. In this scheme, the network weights serve as a parametrization of the restored image. The weights are randomly initialized and fitted to maximize their likelihood given a specific degraded image and a task ...