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20182024
most citedGenerative Adversarial Networks and Perceptual Losses for Video Super-Resolution

167 citations · 188 across the 4 of their papers we have counts for

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eess.IV2024★ 1 cited

A General Method to Incorporate Spatial Information into Loss Functions for GAN-based Super-resolution Models

Xijun Wang, Santiago López-Tapia, Alice Lucas +3

Generative Adversarial Networks (GANs) have shown great performance on super-resolution problems since they can generate more visually realistic images and video frames. However, t…