Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution

Video super-resolution (VSR) has become one of the most critical problems in video processing. In the deep learning literature, recent works have shown the benefits of using adversarial-based and perceptual losses to improve the performance on various image restoration tasks; however, these have yet to be applied for video super-resolution.

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Cite this as

Alice Lucas, Santiago Lopez-Tapia, Rafael Molina, Aggelos K. Katsaggelos (2024). Dataset: Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution. https://doi.org/10.57702/fq54p9n2

DOI retrieved: December 3, 2024

Additional Info

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Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.1109/TIP.2019.2895768
Author Alice Lucas
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Santiago Lopez-Tapia
Rafael Molina
Aggelos K. Katsaggelos
Homepage https://arxiv.org/abs/1805.04652