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Positional Encoding as Spatial Inductive Bias in GANs
Rui Xu, Xintao Wang, Kai Chen +2
SinGAN shows impressive capability in learning internal patch distribution despite its limited effective receptive field. We are interested in knowing how such a translation-invari…
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
Kelvin C. K. Chan, Xintao Wang, Ke Yu +2
Video super-resolution (VSR) approaches tend to have more components than the image counterparts as they need to exploit the additional temporal dimension. Complex designs are not…
GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution
Kelvin C. K. Chan, Xintao Wang, Xiangyu Xu +2
We show that pre-trained Generative Adversarial Networks (GANs), e.g., StyleGAN, can be used as a latent bank to improve the restoration quality of large-factor image super-resolut…
Understanding Deformable Alignment in Video Super-Resolution
Kelvin C. K. Chan, Xintao Wang, Ke Yu +2
Deformable convolution, originally proposed for the adaptation to geometric variations of objects, has recently shown compelling performance in aligning multiple frames and is incr…