574 citations · 1k across the 14 of their papers we have counts for
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cs.CV2017★ 574 cited
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…
cs.CV2017★ 14 cited
Synthetic to Real Adaptation with Generative Correlation Alignment Networks
Xingchao Peng, Kate Saenko
Synthetic images rendered from 3D CAD models are useful for augmenting training data for object recognition algorithms. However, the generated images are non-photorealistic and do…