Knowledge Commons of Institute of Automation,CAS
A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing | |
Zhang, Shifeng1,2; Wang, Xiaobo4; Liu, Ajian3; Zhao, Chenxu4; Wan, Jun1,3; Sergio Escalera5; Shi, Hailin4; Wang, Zezheng4; Li, Stan Z.1,2 | |
2019 | |
会议名称 | IEEE Conference on Computer Vision and Pattern Recognition |
会议日期 | 2019-06 |
会议地点 | 美国长滩 |
摘要 | Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmark datasets in recent years. However, existing face anti-spoofing benchmarks have limited number of subjects (≤170) and modalities (≤2), which hinder the further development of the academic community. To facilitate face anti-spoofing research, we introduce a large-scale multi-modal dataset, namely CASIA-SURF, which is the largest publicly available dataset for face anti-spoofing in terms of both 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). We also provide a measurement set, evaluation protocol and training/validation/testing subsets, developing a new benchmark for face anti-spoofing. Moreover, we present a new multi-modal fusion method as baseline, which performs feature re-weighting to select the more informative channel features while suppressing the less useful ones for each modal. Extensive experiments have been conducted on the proposed dataset to verify its significance and generalization capability. |
收录类别 | EI |
七大方向——子方向分类 | 生物特征识别 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39046 |
专题 | 多模态人工智能系统全国重点实验室_生物识别与安全技术 |
作者单位 | 1.Institute of Automation Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.Macau University of Science and Technology 4.JD 5.Universitat de Barcelona |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Zhang, Shifeng,Wang, Xiaobo,Liu, Ajian,et al. A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing[C],2019. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
0503.pdf(5478KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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