Ginecologia De Gori 2 Edicion.17

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Ginecologia De Gori 2 Edicion.17





 
 
 
 
 
 
 

Ginecologia De Gori 2 Edicion.17

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Máquina de miércoles para recibir mi ginecología.. 2. Zain Oliver 18/10/2014 12:22PM. ginecologia de gori 2 .
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Conclusions {#conclusions.unnumbered}
===========

We proposed a novel GAN architecture for face anti-spoofing for the surveillance use case, which is able to generate unsupervised person-specific anti-spoofing masks. In particular, we proposed a quasi-autoencoder-based architecture that is able to perform an unsupervised person-specific image classification in a given image, and then we use it to perform a conditional training of a segmentation model for the generation of anti-spoofing masks for that particular class. Our approach consists of a completely unsupervised training and a subsequent application of our method to a given person, which is a significant improvement over current unsupervised/semi-supervised approaches that require only a weak labels or human masks. Further, the proposed architecture exploits the low-level face features for enhancing the PSM generation, which we showed to improve its accuracy. We also performed extensive experiments to evaluate our approach and our generative model. The experimental results demonstrated that the proposed GAN-based generative model is able to generate anti-spoofing masks for the target person with good performances. Besides, the experiment results also demonstrated the importance of the use of the conditional GANs for the generation of pseudo masks. These findings are very promising, and we believe that the proposed method constitutes a significant step towards the research field of deep unsupervised learning and its applications in the field of face anti-spoofing. In this research, we only proposed a general architecture, and focused on the training of the data. Nevertheless, the generative

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