Release Agreement for ROSE-Youtu Face Liveness Detection Dataset

ROSE-Youtu Face Liveness Detection Database is a new and comprehensive face anti-spoofing database, which covers a large variety of illumination conditions, camera models, and attack types. The ROSE-Youtu Face Liveness Detection Database (ROSE-Youtu) consists of 3350 videos with 20 subjects totaling 5.45GB in size.

We consider three spoofing attack types including printed paper attack, video replay attack, and masking attack. For printed paper attack, face image with still printed paper and quivering printed paper (A4 size) are used. For video replay attack, we display a face video on Lenovo LCD screen and Mac screen. For masking attack, masks with and without cropping are considered. Moreover, the face videos are captured with different backgrounds which guarantee the face videos are coupled with different illumination conditions. To keep consistent with the genuine face video, the standoff distance between spoofing medium and camera is also about 30-50 cm.

Usage for Academic Reseach

Terms and Conditions:

The use of this dataset is governed by the following terms and conditions:

Related Publications

Please kindly cite the following reference if you use the dataset: Haoliang Li, Wen Li, Hong Cao, Shiqi Wang, Feiyue Huang and Alex C. Kot, “Unsupervised Domain Adaptation for Face Anti-Spoofing”, IEEE Transactions on Information Forensics and Security (in press).

By completing this online form, you have accepted the above terms & conditions and agree to include the above acknowledgements in your publications.

We need to validate all requests. Therefore we require you to provide full name of organisation and affiliated email address.

Project Title
Requester's Details
First Name Last Name
Designation example: post-graduate student, research associate, research fellow, faculty, system analyst, data scientist
Email Address
Supervisor's Details (Leave all fields below blank if Supervisor is same as Requester)
First Name Last Name
Email Address
Designation example: research fellow, faculty, lead data scientist, chief data officer