Welcome to Multi-modal Face Anti-spoofing Attack Detection Challenge@CVPR2019
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 future face Anti-spoofing research, we release a large-scale multi-modal dataset, namely Chalearn 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).
More information can be found in our paper:
- Shifeng Zhang, Xiaobo Wang, Ajian Liu, Chenxu Zhao, Jun Wan, Sergio Escalera, Hailin Shi, Zezheng Wang, Stan Z. Li, " A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing ", CVPR, 2019 (accpeted).
If you are interested in the CASIA-SURF dataset or the challenge in CVPR workshop 2019, please cite this paper.
Our challenge begins on Dec 22, 2018 ( codalab link), which will be hold on CVPR 2019 workshop. Winners and best papers will be awarded in cash (Baidu have confirmed to sponsor our CVPR 2019 workshop). We will organize a special issue in top journal (pending) and will also invite winners to submit their papers in it.
Full Schedule of Face Spoofing Workshop@CVPR2019
Date: June 17, 2019 (Monday); Location: 102B
9:00 - 9:20 Opening of contest; Overview of results; Awards ceremony
9:20 - 10:10 Keynote Speaker: Stan Z. Li (Institute of Automation , Chinese Academy of Sciences)
10:10 - 10:30 Aleksandr Parkin et al, "Recognizing Multi-modal Face Spoofing with Face Recognition Networks" (1st place, best paper)
10:30 - 11:00 Coffee break
11:00 - 11:20 Daniel Perez-Cabo et al, "Deep Anomaly Detection for Generalized Face Anti-spoofing"
11:20 - 11:40 Guoqing Wang et al, "Multi-modal Face Presentation Attack Detection via Spatial and Channel Attentions"
11:40 - 12:30 Keynote Speaker: Abdenour Hadid (University of Oulu, Finland)
14:00 - 14:50 Keynote Speaker: Xiaoming Liu (Michigan State University)
14:50 - 15:10 FaceBagNet: Bag-of-local-features Model for Multi-modal Face Anti-spoofing (2nd place)
15:10 - 15:40 Coffee break
15:40 - 16:30 Keynote Speaker: Guodong Guo (Baidu)
16:30 - 16:50 Peng Zhang et al, "FeatherNets: Convolutional Neural Networks as Ligh as Feather for Face Anti-spoofing"(3rd place)
16:50 - 17:10 Closing
Jun Wan, National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA), email@example.com
Sergio Escalera, Computer Vision Center (UAB) and University of Barcelona, firstname.lastname@example.org
Hugo Jair Escalante, INAOE, ChaLearn, Mexico, email@example.com firstname.lastname@example.org
Isabelle Guyon, Université Paris-Saclay, France, ChaLearn, Berkeley, California, USA, email@example.com
Guodong Guo, IDL, Baidu Research, China, firstname.lastname@example.org
Hailin Shi, JD AI Research, China, email@example.com
Meysam Madadi, Universitat Autonoma de Barcelona & Compter Vision Center, firstname.lastname@example.org
Shaopeng Tang, Beijing SurfingTech Co., Ltd, email@example.com