Image to Image Translation for Domain Adaptation

CVPR 2018 Zak MurezSoheil KolouriDavid KriegmanRavi RamamoorthiKyungnam Kim

We propose a general framework for unsupervised domain adaptation, which allows deep neural networks trained on a source domain to be tested on a different target domain without requiring any training annotations in the target domain. This is achieved by adding extra networks and losses that help regularize the features extracted by the backbone encoder network... (read more)

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