CVPR 2019 Face Spoofing Attrack Workshop and Challenge

[Hugo Jair Escalante]

Call for participation & papers

Chalearn Looking at People series

Face Spoofing Attack Workshop and Challenge 

CVPR Workshop 2019  

Face anti-spoofing detection is an crucial procedure in biometric face recognition systems. Previous competitions (i.e. ICB 2013 facial spoofing attacks, IJCB 2011 facial spoofing attacks, IJCB 2017 competition ) focused on 2D face spoofing attacks, and most published works focus on one single modality, such as rgb or depth face spoofing detection. However, one single modality may not capture rich enough face and environment information. Fortunately, according to the new development of camera sensors, face image with multi modalities are captured conveniently in a low cost.  Therefore, We are organizing an academic competition and workshop focus on multi-modal (RGB+depth+IR) face anti-spoofing detection in videos. A new large-scale multimodal face spoofing attack datasets is released and used in the competition containing more than 2000 recorded subjects with multiple modalities. 

We propose a challenge that aims at compiling the latest efforts and research advances from the computational intelligence community in creating fast and accurate face spoofing detection algorithms. The methods will be evaluated on a large, newly collected and annotated dataset.

The challenges is running in the CodaLab platform (https://competitions.codalab.org/competitions/20853), and results will be presented at the CVPR 2019 ChaLearn LAP associated workshop. Participants obtaining the best results will be invited to submit a paper to associated workshop and extended versions to a dedicated Special Issue in a top tier journal (TBA). There will be prizes and travel grants from BAIDU. We will provide cash, travel grants for top 3 winners (1st: 1000$+500$, 2nd:600$+500$, 3rd: 300$+500$). And the best workshop paper will be also rewarded in cash (500$+500$). 

We also solicit submissions in all aspects of facial biometric systems and attacks. Most notably, the following are the main topics of interest:

• Novel methodologies on anti-spoofing detection in visual information systems. 
  
• Studies on novel attacks to biometric systems, and solutions 
  
• Deep learning methods for biometric authentication systems using visual information
  
• Novel datasets and evaluation protocols on spoofing prevention on visual and multimodal biometric systems
  
• Methods for deception detection from visual and multimodal information
  
• Face antispoof attacks dataset (3D face Mask, multimodal).
  
• Deep analysis reviews on face antispoofing attacks.
  
• Generative models  (e.g. GAN) for spoofing attacks.

We are accepting submissions for revision up to 8 pages (same formatting instructions as CVPR). CMT submissions will be reviewed by 3 members of PC committee.  

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Important dates (tentative)

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Important dates competition:

• 20th November, 2018: Beginning of the quantitative competition, release of development and validation data.
• 10th March, 2019: Release of encrypted final evaluation data. Participants can start training their methods with the whole data set.
• 15th March, 2019: Deadline for code submission.
• 16th March, 2019: Release of final evaluation data decryption key. Participants start predicting the results on the final evaluation data.
• 20th March, 2019: End of the quantitative competition. Deadline for submitting the predictions over the final evaluation data. The organizers start the code verification by running it on the final evaluation data.
• 22nd March, 2019: Deadline for submitting the fact sheets.
• 25th March, 2019: Release of the verification results to the participants for review. Participants are invited to follow the paper submission guide for submitting contest papers.
• 30th March, 2017: Paper submission deadline for submitting their CVPRW paper (following workshop dates).

Important dates workshop:

• 30th March, 2019:        Paper submission deadline
• 5th April, 2019:      Paper notification
• 9th April, 2019:     Camera ready

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Organizing team

Jun Wan, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences

Sergio Escalera, Computer Vision Center (UAB) and University of Barcelona

Hugo Jair Escalante, INAOE, ChaLearn, Mexico

Isabelle Guyon, Université Paris-Saclay, France, ChaLearn, Berkeley, California, USA

Guodong Guo, IDL, Baidu Research

Hailin Shi, JD AI Research

Meysam Madadi, Universitat Autonoma de Barcelona & Compter Vision Center

Shaopeng Tang, Beijing SurfingTech Co., Ltd, 

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Hugo Jair Escalante,
Computer Science Department,
National Institute of Astrophysics, Optics and Electronics
Luis Enrique Erro # 1, Tonantzintla, 72840, Puebla, México
hugo...@gmail.com, hugo...@inaoep.mx
http://ccc.inaoep.mx/~hugojair/ http://hugojair.org/