574 citations · 585 across the 5 of their papers we have counts for
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Evaluation of Correctness in Unsupervised Many-to-Many Image Translation
Dina Bashkirova, Ben Usman, Kate Saenko
Given an input image from a source domain and a guidance image from a target domain, unsupervised many-to-many image-to-image (UMMI2I) translation methods seek to generate a plausi…
Adversarial Self-Defense for Cycle-Consistent GANs
Dina Bashkirova, Ben Usman, Kate Saenko
The goal of unsupervised image-to-image translation is to map images from one domain to another without the ground truth correspondence between the two domains. State-of-art method…
Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation
Xingchao Peng, Ben Usman, Kuniaki Saito +3
Unsupervised transfer of object recognition models from synthetic to real data is an important problem with many potential applications. The challenge is how to "adapt" a model tra…
Unsupervised Video-to-Video Translation
Dina Bashkirova, Ben Usman, Kate Saenko
Unsupervised image-to-image translation is a recently proposed task of translating an image to a different style or domain given only unpaired image examples at training time. In t…
VisDA: The Visual Domain Adaptation Challenge
Xingchao Peng, Ben Usman, Neela Kaushik +3
We present the 2017 Visual Domain Adaptation (VisDA) dataset and challenge, a large-scale testbed for unsupervised domain adaptation across visual domains. Unsupervised domain adap…