Competition

Evaluation Criteria

Evaluation Criteria

Considering face anti-spoof as binary classification, we can leverage FPR@TPR as evaluation criteria. Specifically, spoof class is Positive, live class is Negative.

• False Positive Rate (FPR):

FPR = FP / (FP + TN)

• True Positive Rate (TPR):

TPR = TP / (TP + FN)

The TPR@FPR=5E-3 determines the final ranking. Besides, we also provide TPR@FPR=10E-3 and TPR@FPR=10E-4. If TPR@FPR=5E-3 is the same, the one with higher TPR@FPR=10E-4 will achieve a higher ranking

Terms and Conditions

General Rules

The CelebA-Spoof Challenge 2020 will be around 9 weeks (64 days) with one phase. The challenge will start together with ECCV 2020, The 2nd Workshop on Sensing, Understanding and Synthesizing Humans. Participants are restricted to train their algorithms on the publicly available CelebA-Spoof training dataset. The hidden test set used for online evaluation contains around 30000 images, which represents the general circumstances of the hidden test set and is used to maintain a public leaderboard. The final results will be revealed around Nov. 2020. Participants are expected to develop more robust and generalized methods for face anti-spoofing detection in real-world scenarios.

When participating in the competition, please be reminded that:

• Results in the correct format must be uploaded to the evaluation server. The evaluation page lists detailed information regarding how results will be evaluated.
• Each entry must be associated with a team and provide its affiliation.
• (tentative) The online evaluation results must be submitted through this CodaLab competition site of the CelebA-Spoof Challenge. The online evaluation chances will be updated on Friday, 11:59 p.m (UTC) every week. The participants can conduct 5 online evaluations (each with 40 minutes of runtime limit) per week Each participant will be assigned 1 Tesla V100 GPU with 16 GB memory capacity. The organizer will offer some hints/codes to ensure a successful submission.
• Using multiple accounts to increase the number of submissions and private sharing outside teams are strictly prohibited.
• The organizer reserves the absolute right to disqualify entries which are incomplete or illegible, late entries, or entries that violate the rules.
• The organizer reserves the right to adjust the competition schedule and rules based on situations.
• The best entry of each team will be public in the leaderboard at all times.
• To compete for awards, the participants must fill out a fact sheet briefly describing their methods. There is no other publication requirement.

Terms of Use: CelebA-Spoof Dataset

Before downloading and using the CelebA-Spoof dataset, please agree to the following terms of use. You, your employer and your affiliations are referred to as "User". The authors and their affiliations, SenseTime, are referred to as "Producer".

• The CelebA-Spoof dataset is used for non-commercial/non-profit research purposes only.
• All the images in CelebA-Spoof dataset can be used for academic purposes. However, the Producer is NOT responsible for any further use in a defamatory, pornographic, or any other unlawful manner, or violation of any applicable regulations or laws.
• The User takes full responsibility for any consequence caused by his/her use of CelebA-Spoof dataset in any form and shall defend and indemnify the Producer against all claims arising from such uses.
• The User should NOT distribute, copy, reproduce, disclose, assign, sublicense, embed, host, transfer, sell, trade, or resell any portion of the CelebA-Spoof dataset to any third party for any purpose.
• The User can provide his/her research associates and colleagues with access to CelebA-Spoof dataset (the download link or the dataset itself) provided that he/she agrees to be bound by these terms of use and guarantees that his/her research associates and colleagues agree to be bound by these terms of use.
• The User should NOT remove or alter any copyright, trademark, or other proprietary notices appearing on or in copies of the CelebA-Spoof dataset.
• This agreement is effective for any potential User of the CelebA-Spoof dataset upon the date that the User first accesses the CelebA-Spoof dataset in any form.
• The Producer reserves the right to terminate the User's access to the CelebA-Spoof dataset at any time.
• For using CelebA-Spoof dataset, please cite the following paper:

  @inproceedings{CelebA-Spoof,
    title={CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich Annotations},
    author={Zhang, Yuanhan and Yin, Zhenfei and Li, Yidong and Yin, Guojun and Yan, Junjie and Shao, Jing and Liu, Ziwei},
    booktitle={European Conference on Computer Vision (ECCV)},
    year={2020}
  }
  

The download link will be sent to you once your request is approved.

Software

Copyright © 2020, CelebA-Spoof Consortium. All rights reserved. Redistribution and use software in source and binary form, with or without modification, are permitted provided that the following conditions are met:

• Redistributions of source code must retain the above copyright notice, this list of conditions, and the following disclaimer.
• Redistributions in binary form must reproduce the above copyright notice, this list of conditions, and the following disclaimer in the documentation and/or other materials provided with the distribution.
• Neither the name of the CelebA-Spoof Consortium nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE AND ANNOTATIONS ARE PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.