Paper

In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks

In unsupervised image-to-image translation, the goal is to learn the mapping between an input image and an output image using a set of unpaired training images. In this paper, we propose an extension of the unsupervised image-to-image translation problem to multiple input setting... (read more)

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