T
Taesung Park
Researcher at University of California, Berkeley
Publications - 19
Citations - 22146
Taesung Park is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Computer science & Image translation. The author has an hindex of 10, co-authored 13 publications receiving 16128 citations.
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Proceedings ArticleDOI
Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks
TL;DR: CycleGAN as discussed by the authors learns a mapping G : X → Y such that the distribution of images from G(X) is indistinguishable from the distribution Y using an adversarial loss.
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Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
TL;DR: This work presents an approach for learning to translate an image from a source domain X to a target domain Y in the absence of paired examples, and introduces a cycle consistency loss to push F(G(X)) ≈ X (and vice versa).
Proceedings Article
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman,Eric Tzeng,Taesung Park,Jun-Yan Zhu,Phillip Isola,Kate Saenko,Alexei A. Efros,Trevor Darrell +7 more
TL;DR: A novel discriminatively-trained Cycle-Consistent Adversarial Domain Adaptation model that adapts representations at both the pixel-level and feature-level, enforces cycle-consistency while leveraging a task loss, and does not require aligned pairs is proposed.
Proceedings ArticleDOI
Semantic Image Synthesis With Spatially-Adaptive Normalization
TL;DR: S spatially-adaptive normalization is proposed, a simple but effective layer for synthesizing photorealistic images given an input semantic layout that allows users to easily control the style and content of image synthesis results as well as create multi-modal results.
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Contrastive Learning for Unpaired Image-to-Image Translation
TL;DR: The framework enables one-sided translation in the unpaired image-to-image translation setting, while improving quality and reducing training time, and can be extended to the training setting where each "domain" is only a single image.