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Extremely Weak Supervised Image-to-Image Translation for Semantic Segmentation
[article]
2019
arXiv
pre-print
Recent advances in generative models and adversarial training have led to a flourishing image-to-image (I2I) translation literature. The current I2I translation approaches require training images from the two domains that are either all paired (supervised) or all unpaired (unsupervised). In practice, obtaining paired training data in sufficient quantities is often very costly and cumbersome. Therefore solutions that employ unpaired data, while less accurate, are largely preferred. In this
arXiv:1909.08542v1
fatcat:o34fdgz4fnbqbajflrh5jnf424