The Surprising Effectiveness of Linear Unsupervised Image-to-Image Translation

24 Jul 2020 Eitan Richardson Yair Weiss

Unsupervised image-to-image translation is an inherently ill-posed problem. Recent methods based on deep encoder-decoder architectures have shown impressive results, but we show that they only succeed due to a strong locality bias, and they fail to learn very simple nonlocal transformations (e.g. mapping upside down faces to upright faces)... (read more)

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