A Generative Adversarial Approach with Residual Learning for Dust and Scratches Artifacts Removal-Reference-Cited by-同舟云学术

A Generative Adversarial Approach with Residual Learning for Dust and Scratches Artifacts Removal

Published:2020-10-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2nd Workshop on Structuring and Understanding of Multimedia heritAge Contents
language:
Short-container-title:

Author:

Mironică Ionuţ¹

Affiliation:

1. Adobe Research Romania, Bucharest, Romania

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3423323.3423411

Reference26 articles.

1. Comprehensive solutions for automatic removal of dust and scratches from images

2. Detection and Tracking Scheme for Line Scratch Removal in an Image Sequence

3. Blotch and scratch removal in archived film using a semi-transparent corruption model and a ground-truth generation technique

4. Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In Advances in neural information processing systems. 2672--2680. Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In Advances in neural information processing systems. 2672--2680.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Image Inpainting Using PatchGAN;2023 3rd International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA);2023-12-13

2. Simulating analogue film damage to analyse and improve artefact restoration on high‐resolution scans;Computer Graphics Forum;2023-05