Flow-based Image-to-Image Translation with Feature Disentanglement

Ruho Kondo, Keisuke Kawano, Satoshi Koide, Takuro Kutsuna

Neural Information Processing Systems 

Tothisendweproposeaflow-based image-to-image model, called FlowU-Net with Squeeze modules (FUNS), that allows us to disentangle the features while retaining the ability to generate highquality diverse images from condition images.

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