Publication

Deeply Vulnerable -- a study of the robustness of face recognition to presentation attacks

Related publications (35)

About
Privacy
Disclaimer

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Deeply Vulnerable -- a study of the robustness of face recognition to presentation attacks

Graph Chatbot

Chat with Graph Search

Deep Learning Generalization with Limited and Noisy Labels

Leveraging Unlabeled Data to Track Memorization

EpilepsyNet: Interpretable Self-Supervised Seizure Detection for Low-Power Wearable Systems

Regularization of polynomial networks for image recognition

Regularization of polynomial networks for image recognition

BLACK-BOX ATTACKS ON IMAGE ACTIVITY PREDICTION AND ITS NATURAL LANGUAGE EXPLANATIONS

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

The spectral bias of polynomial neural networks

On the robustness of randomized classifiers to adversarial examples

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

BLACK-BOX ATTACKS ON IMAGE ACTIVITY PREDICTION AND ITS NATURAL LANGUAGE EXPLANATIONS

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

The spectral bias of polynomial neural networks

Regularization of polynomial networks for image recognition

Regularization of polynomial networks for image recognition

On the robustness of randomized classifiers to adversarial examples

Deep Learning Generalization with Limited and Noisy Labels

Leveraging Unlabeled Data to Track Memorization

EpilepsyNet: Interpretable Self-Supervised Seizure Detection for Low-Power Wearable Systems