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We collect and annotate spoof images of CelebA-Spoof. Among 43 rich attributes, 40 attributes belong to Live images including all facial components and accessories such as skin, nose, eyes, eyebrows, lip, hair, hat, eyeglass. CelebA-Spoof can be used to train and evaluate algorithms of face anti-spoofing.

Registration is now open. If you are interested in soliciting new ideas to advance the state of the art in real-world face anti-spoofing, we look forward to your participation! The CelebA-Spoof Challenge submission example is avaliable here. We hired 8 collectors to collect spoof data and another 2 annotators to refine labeling for all data.

To improve the generalization and diversity of the dataset, as shown in Figure below, we define three collection dimensions with fine-grained quantities:.

To further comprehensively investigate face anti-spoofing tasks from various perspectives, in CelebA-Spoof, we annotate 43 different annotations. Based on these rich attributes, we further propose a simple yet powerful multi-task framework, namely AENet. Through AENet,we conduct extensive experiments to explore the roles of semantic informationand geometric information in face anti-spoofing. Face on Mars. Categories : Face of Mars Cursed images.

Namespaces File Discussion. Views View Edit History. Main page Welcome Community portal Village pump Help center. Upload file Recent changes Latest files Random file Contact us. Download as PDF Printable version. Description Face-on-mars. Transferred from en. Hu, X. He, and J. In ECCV He, X. Zhang, S. Ren, and J. Deep residual learning for image recognition. In CVPR Chen, J. Yao, R. Zhou, T. Qin, T. Zhan and Q. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of ODNI, IARPA, or the U.

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