A Diverse Large-scale Dataset for Evaluating Rebroadcast Attacks
نویسندگان
چکیده
We describe the acquisition of a large, diverse set of rebroadcast images captured by a screen-grab, scanning a printed photo, or rephotographing a displayed or a printed photo. This dataset consists of 14, 500 rebroadcast images captured from a diverse set of devices: 234 displays, 173 scanners, 282 printers, and 180 recapture cameras. The diversity of this dataset—across devices and types of rebroadcast—poses significant challenges to detecting rebroadcast attacks. We evaluate the efficacy of four different classifiers trained to simultaneously detect all types of rebroadcast images.
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