Multimodal Unsupervised Image-to-Image Translation

ECCV 2018 Xun HuangMing-Yu LiuSerge BelongieJan Kautz

Unsupervised image-to-image translation is an important and challenging problem in computer vision. Given an image in the source domain, the goal is to learn the conditional distribution of corresponding images in the target domain, without seeing any pairs of corresponding images... (read more)

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Task Dataset Model Metric name Metric value Global rank Compare
Multimodal Unsupervised Image-To-Image Translation Cats-and-Dogs MUNIT CIS 1.039 # 1
Multimodal Unsupervised Image-To-Image Translation Cats-and-Dogs MUNIT IS 1.050 # 1
Multimodal Unsupervised Image-To-Image Translation Edge-to-Handbags MUNIT Quality 50.0% # 2
Multimodal Unsupervised Image-To-Image Translation Edge-to-Handbags MUNIT Diversity 0.175 # 1
Multimodal Unsupervised Image-To-Image Translation Edge-to-Shoes MUNIT Quality 50.0% # 2
Multimodal Unsupervised Image-To-Image Translation Edge-to-Shoes MUNIT Diversity 0.109 # 1