The Elephant in the Room: The Problems that Privacy-Preserving ML Can´t Solve

NeurIPS 2020

The Elephant in the Room: The Problems that Privacy-Preserving ML Can´t Solve

Dec 06, 2020
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We showcase a family of common failures of state-of-the art object detectors. These are obtained by replacing image sub-regions by another sub-image that contains a trained object. We call this "object transplanting". Modifying an image in this manner is shown to have a non-local impact on object detection. Slight changes in object position can affect its identity according to an object detector as well as that of other objects in the image. We provide some analysis and suggest possible reasons for the reported phenomena. Speakers: Katrina Ligett

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