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ImageNet-D: A new challenging robustness dataset inspired by domain adaptation
Evgenia Rusak · Steffen Schneider · Peter V Gehler · Oliver Bringmann · Wieland Brendel · Matthias Bethge
Event URL: https://openreview.net/forum?id=LiC2vmzbpMO »
We propose a new challenging dataset to benchmark robustness of ImageNet-trained models: ImageNet-D. ImageNet-D has six different domains (Real'',Painting'', Clipart'',Sketch'', Infograph'' andQuickdraw''). We show that even state-of-the-art models struggle on this dataset and find that they make well-interpretable errors.
Author Information
Evgenia Rusak (University of Tuebingen)
Steffen Schneider (University of Tuebingen / EPFL / ELLIS)
Peter V Gehler (Amazon)
Oliver Bringmann (University of Tübingen)
Wieland Brendel (University of Tübingen)
Matthias Bethge (University of Tübingen)
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