DiffGAR: Model-Agnostic Restoration from Generative Artifacts Using Image-to-Image Diffusion Models-Reference-Cited by-同舟云学术

DiffGAR: Model-Agnostic Restoration from Generative Artifacts Using Image-to-Image Diffusion Models

Published:2022-12-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 6th International Conference on Computer Science and Artificial Intelligence
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Author:

Yin Yueqin¹^ORCID,Huang Lianghua²^ORCID,Liu Yu²^ORCID,Huang Kaiqi¹^ORCID

Affiliation:

1. School of Artificial Intelligence, University of Chinese Academy of Sciences, China and Institute of Automation, Chinese Academy of Sciences, China

2. Machine Intelligence Technology Lab, Alibaba Group, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3577530.3577539

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3. Jooyoung Choi Jungbeom Lee Chaehun Shin Sungwon Kim Hyunwoo Kim and Sungroh Yoon. 2022. Perception Prioritized Training of Diffusion Models. CVPR. Jooyoung Choi Jungbeom Lee Chaehun Shin Sungwon Kim Hyunwoo Kim and Sungroh Yoon. 2022. Perception Prioritized Training of Diffusion Models. CVPR.

4. Yunjey Choi Youngjung Uh Jaejun Yoo and Jung-Woo Ha. 2020. Stargan v2: Diverse image synthesis for multiple domains. CVPR. Yunjey Choi Youngjung Uh Jaejun Yoo and Jung-Woo Ha. 2020. Stargan v2: Diverse image synthesis for multiple domains. CVPR.

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