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http://hdl.handle.net/10397/107159
Title: | Image super-resolution via attention based back projection networks | Authors: | Liu, ZS Wang, LW Li, CT Siu, WC Chan, YL |
Issue Date: | 2019 | Source: | In Proceedings of 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 27-28 October 2019, Seoul, Korea (South), p. 3517-3525 | Abstract: | Deep learning based image Super-Resolution (SR) has shown rapid development due to its ability of big data digestion. Generally, deeper and wider networks can extract richer feature maps and generate SR images with remarkable quality. However, the more complex network we have, the more time consumption is required for practical applications. It is important to have a simplified network for efficient image SR. In this paper, we propose an Attention based Back Projection Network (ABPN) for image super-resolution. Similar to some recent works, we believe that the back projection mechanism can be further developed for SR. Enhanced back projection blocks are suggested to iteratively update low-and high-resolution feature residues. Inspired by recent studies on attention models, we propose a Spatial Attention Block (SAB) to learn the cross-correlation across features at different layers. Based on the assumption that a good SR image should be close to the original LR image after down-sampling. We propose a Refined Back Projection Block (RBPB) for final reconstruction. Extensive experiments on some public and AIM2019 Image Super-Resolution Challenge datasets show that the proposed ABPN can provide state-of-the-art or even better performance in both quantitative and qualitative measurements. | Publisher: | Institute of Electrical and Electronics Engineers | ISBN: | 978-1-7281-5023-9 (Electronic) 978-1-7281-5024-6 (Print on Demand(PoD)) |
DOI: | 10.1109/ICCVW.2019.00436 | Description: | 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 27-28 October 2019, Seoul, Korea (South) | Rights: | ©2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication Z. -S. Liu, L. -W. Wang, C. -T. Li, W. -C. Siu and Y. -L. Chan, "Image Super-Resolution via Attention Based Back Projection Networks," 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), Seoul, Korea (South), 2019, pp. 3517-3525 is available at https://doi.org/10.1109/ICCVW.2019.00436. |
Appears in Collections: | Conference Paper |
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