Publication

Learning One Class Representations for Presentation Attack Detection using Multi-channel Convolutional Neural Networks

Related publications (42)

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.

Learning One Class Representations for Presentation Attack Detection using Multi-channel Convolutional Neural Networks

Graph Chatbot

Chat with Graph Search

Discriminative Deep Feature Visualization for Explainable Face Recognition

Towards Visual Saliency Explanations of Face Verification

Recognizing distant faces

Face Reconstruction Fromdeep Facial Embeddings Using A Convolutional Neural Network

A Novel Framework for Assessment of Deep Face Recognition Systems in Realistic Conditions

Personalized Productive Engagement Recognition in Robot-Mediated Collaborative Learning

On the Recognition Performance of BioHashing on state-of-the-art Face Recognition models

Learning One Class Representations for Face Presentation Attack Detection using Multi-channel Convolutional Neural Networks

Trustworthy Face Recognition: Improving Generalization of Deep Face Presentation Attack Detection

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion