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Deep Learning for Image/Video Restoration and Super-resolution
2022
Foundations and Trends in Computer Graphics and Vision
Recent advances in neural signal processing led to significant improvements in the performance of learned image/video restoration and super-resolution (SR). An important benefit of data-driven deep learning approaches to image processing is that neural models can be optimized for any differentiable loss function, including perceptual loss functions, leading to perceptual image/video restoration and SR, which cannot be easily handled by traditional model-based methods. We start with a brief
doi:10.1561/0600000100
fatcat:5keqxf3lingubhlgrptdpq42xy