Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

CVPR 2017 Konstantinos BousmalisNathan SilbermanDavid DohanDumitru ErhanDilip Krishnan

Collecting well-annotated image datasets to train modern machine learning algorithms is prohibitively expensive for many tasks. One appealing alternative is rendering synthetic data where ground-truth annotations are generated automatically... (read more)

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