Image-to-image Mapping with Many Domains by Sparse Attribute Transfer

CVPR 2020
Published: Jun 23, 2020
Abstract
Unsupervised image-to-image translation consists of learning a pair of mappings between two domains without known pairwise correspondences between points. The current convention is to approach this task with cycle-consistent GANs: using a discriminator to encourage the generator to change the image to match the target domain, while training the generator to be inverted with another mapping. While ending up with paired inverse functions may be a...
Paper Details
Title
Image-to-image Mapping with Many Domains by Sparse Attribute Transfer
Published Date
Jun 23, 2020
Journal
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