REAP is a digital benchmark that allows the user to evaluate patch attacks on real images, and under real-world conditions. Built on top of the Mapillary Vistas dataset, the benchmark contains over 14,000 traffic signs. Each sign is augmented with a pair of geometric and lighting transformations, which can be used to apply a digitally generated patch realistically onto the sign.
Source: REAP: A Large-Scale Realistic Adversarial Patch BenchmarkPaper | Code | Results | Date | Stars |
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