Comprised of real human and wax figure images and videos that endorse the problem of face spoofing detection. The dataset consists of more than 1800 face images and 110 videos of 55 people/waxworks, arranged in training, validation and test sets with a large range in expression, illumination and pose variations
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Dataset for face anti-spoofing in terms of both subjects and modalities. Specifically, it consists of subjects with videos and each sample has modalities (i.e., RGB, Depth and IR).
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The Oulu-NPU face presentation attack detection database consists of 4950 real access and attack videos. The 2D face artefacts were created using two printers and two display devices. The videos of the 55 subjects are divided into three subject-disjoint subsets for training, development and testing. Four test protocols are used to evaluate the generalization capability of face PAD methods across three covariates: unknown environmental conditions (namely illumination and background scene), acquisition
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The Replay-Mobile Database for face spoofing consists of 1190 video clips of photo and video attack attempts to 40 clients, under different lighting conditions.
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…The WMCA database is produced at Idiap within the framework of “IARPA BATL” and “H2020 TESLA” projects and it is intended for investigation of presentation attack detection (PAD) methods for face recognition
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