Spatially Adaptive Losses for Video Super-resolution with GANs

Spatially Adaptive Losses for Video Super-resolution with GANs. Wang, X., Lucas, A., Lopez-Tapia, S., Wu, X., Molina, R., & Katsaggelos, A. K. In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), volume 2019-May, pages 1697–1701, may, 2019. IEEE.

Paper doi abstract bibtex

Deep Learning techniques and more specifically Generative Adversarial Networks (GANs) have recently been used for solving the video super-resolution (VSR) problem. In some of the published works, feature-based perceptual losses have also been used, resulting in promising results. While there has been work in the literature incorporating temporal information into the loss function, studies which make use of the spatial activity to improve GAN models are still lacking. Towards this end, this paper aims to train a GAN guided by a spatially adaptive loss function. Experimental results demonstrate that the learned model achieves improved results with sharper images, fewer artifacts and less noise.

@inproceedings{Xijun2019a,
abstract = {Deep Learning techniques and more specifically Generative Adversarial Networks (GANs) have recently been used for solving the video super-resolution (VSR) problem. In some of the published works, feature-based perceptual losses have also been used, resulting in promising results. While there has been work in the literature incorporating temporal information into the loss function, studies which make use of the spatial activity to improve GAN models are still lacking. Towards this end, this paper aims to train a GAN guided by a spatially adaptive loss function. Experimental results demonstrate that the learned model achieves improved results with sharper images, fewer artifacts and less noise.},
author = {Wang, Xijun and Lucas, Alice and Lopez-Tapia, Santiago and Wu, Xinyi and Molina, Rafael and Katsaggelos, Aggelos K.},
booktitle = {ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
doi = {10.1109/ICASSP.2019.8682742},
isbn = {978-1-4799-8131-1},
issn = {15206149},
keywords = {Generative Adversarial Networks,Perceptual Loss,Spatial Adaptivity,Video Super-Resolution},
month = {may},
pages = {1697--1701},
publisher = {IEEE},
title = {{Spatially Adaptive Losses for Video Super-resolution with GANs}},
url = {https://ieeexplore.ieee.org/document/8682742/},
volume = {2019-May},
year = {2019}
}

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