In this challenge, we will release a largest cross-ethnicity dataset CASIA-SURF CeFA for face antispoofing (please refer to ). It includes four protocols. But for this challenge, we have two tracks and only use protocol 4 (Cross-ethnicity & PAI) .
- Track 1 (Multi-modal data): It uses the protocol 4 (Cross-ethnicity & PAI) in . Participates can use multiply modalities, such as RGB, depth and IR data. Any extra data or pretrained model cannot be used in track 1 (link).
- Track 2 (Single RGB modal data): It uses the protocol protocol 4 (Cross-ethnicity & PAI) in . But participates are only permitted to use the single RGB modality. Any extra data or pretrained model cannot be used in track 2 (link).
Dataset Application [link]
Full Schedule of Workshop@CVPR2020
- Jun Wan (万军), NLPR, Institute of Automation, Chinese Academy of Sciences (CASIA), China, firstname.lastname@example.org
- Ajian Liu, Macau University of Science and Technology (M.U.S.T.), Macau, China, email@example.com
- Sergio Escalera, Computer Vision Center (UAB) and University of Barcelona, Spain, firstname.lastname@example.org
- Hugo Jair Escalante, INAOE, ChaLearn, Mexico, email@example.com
- Isabelle Guyon, Université Paris-Saclay, France and ChaLearn, Berkeley, California, USA, firstname.lastname@example.org
- Guodong Guo, IDL, Baidu Research, China, email@example.com
- Shaopeng Tang, Beijing Surfing Technology Ltd, firstname.lastname@example.org
- Baidu (the exclusive sponsorship)
Ajian Liu, Zichang Tan, Xuan Li, Jun Wan*, Sergio Escalera, Guodong Guo, Stan Z. Li, " Static and Dynamic Fusion for Multi-modal Cross-ethnicity Face Anti-spoofing ", arxiv, 2019.