Dataset description

To facilitate future face Anti-spoofing research, we release a large-scale multi-modal dataset, namely Chalearn CASIA-SURF[1], which is the largest publicly available dataset for face Anti-spoofing both in terms of subjects and visual modalities. Specifically, it consists of 1, 000 subjects with 21, 000 videos and each sample has 3 modalities (i.e., RGB, Depth and IR). More information can be found here.


[1] Shifeng Zhang, Xiaobo Wang, Ajian Liu, Chenxu Zhao, Jun Wan, Sergio Escalera, Hailin Shi, Zezheng Wang, Stan Z. Li, " CASIA-SURF: A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing ", arXiv, 2018


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