Residual Local Feature Network for Efficient Super-Resolution-Reference-Cited by-同舟云学术

Residual Local Feature Network for Efficient Super-Resolution

Published:2022-06 Issue: Volume: Page:
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Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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Author:

Kong Fangyuan¹,Li Mingxi¹,Liu Songwei¹,Liu Ding¹,He Jingwen¹,Bai Yang¹,Chen Fangmin¹,Fu Lean¹

Affiliation:

1. ByteDance Inc

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9856930/9856648/09857179.pdf?arnumber=9857179

Reference49 articles.

1. Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

2. Single image super-resolution via a holistic attention network;niu;Computer Vision - ECCV 2020 - 16th European Conference Glasgow UK August 23-28 2020 Proceedings Part XII volume 12357 of Lecture Notes in Computer Science,2020

3. Generic Perceptual Loss for Modeling Structured Output Dependencies

4. Residual Feature Aggregation Network for Image Super-Resolution

5. Residual feature distillation network for lightweight image super-resolution;liu;Computer Vision - ECCV 2020 Workshops - Glasgow UK August 23-28 2020 Proceedings Part III volume 12537 of Lecture Notes in Computer Science,2020

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