Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression

• URL: http://arxiv.org/abs/2102.06531v1
• Date: Tue, 9 Feb 2021 11:24:20 GMT
• Title: Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression
• Authors: A. Murat Tekalp, Michele Covell, Radu Timofte, Chao Dong
• Abstract summary: This special issue covers the state of the art in learned image/video restoration and compression. Recent works have shown that learned models can achieve significant performance gains.
• Score: 87.64420920726998
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Recent works have shown that learned models can achieve significant performance gains, especially in terms of perceptual quality measures, over traditional methods. Hence, the state of the art in image restoration and compression is getting redefined. This special issue covers the state of the art in learned image/video restoration and compression to promote further progress in innovative architectures and training methods for effective and efficient networks for image/video restoration and compression.

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