Search Results for author: Sebastien Marcel

Found 12 papers, 8 papers with code

Prepended Domain Transformer: Heterogeneous Face Recognition without Bells and Whistles

2 code implementations12 Oct 2022 Anjith George, Amir Mohammadi, Sebastien Marcel

The core idea of the proposed approach is to add a novel neural network block called Prepended Domain Transformer (PDT) in front of a pre-trained face recognition (FR) model to address the domain gap.

Contrastive Learning Face Recognition +1

A Comprehensive Evaluation on Multi-channel Biometric Face Presentation Attack Detection

no code implementations21 Feb 2022 Anjith George, David Geissbuhler, Sebastien Marcel

Having a lot of sensors increases the cost of the system, and therefore an understanding of the performance of different sensors against a wide variety of attacks is necessary while selecting the modalities.

Face Presentation Attack Detection Face Recognition

Cross Modal Focal Loss for RGBD Face Anti-Spoofing

1 code implementation CVPR 2021 Anjith George, Sebastien Marcel

Automatic methods for detecting presentation attacks are essential to ensure the reliable use of facial recognition technology.

Face Anti-Spoofing

On the Effectiveness of Vision Transformers for Zero-shot Face Anti-Spoofing

1 code implementation16 Nov 2020 Anjith George, Sebastien Marcel

Although various methods have been suggested for detecting such attacks, most of them over-fit the training set and fail in generalizing to unseen attacks and environments.

Face Anti-Spoofing Face Recognition +1

The High-Quality Wide Multi-Channel Attack (HQ-WMCA) database

no code implementations21 Sep 2020 Zohreh Mostaani, Anjith George, Guillaume Heusch, David Geissbuhler, Sebastien Marcel

The High-Quality Wide Multi-Channel Attack database (HQ-WMCA) database extends the previous Wide Multi-Channel Attack database(WMCA), with more channels including color, depth, thermal, infrared (spectra), and short-wave infrared (spectra), and also a wide variety of attacks.

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

1 code implementation22 Jul 2020 Anjith George, Sebastien Marcel

The proposed system is evaluated on the publicly available WMCA multi-channel face PAD database, which contains a wide variety of 2D and 3D attacks.

Face Anti-Spoofing Face Presentation Attack Detection +2

Deep Models and Shortwave Infrared Information to Detect Face Presentation Attacks

no code implementations22 Jul 2020 Guillaume Heusch, Anjith George, David Geissbuhler, Zohreh Mostaani, Sebastien Marcel

Conducted experiments show superior performance over similar models acting on either color images or on a combination of different modalities (visible, NIR, thermal and depth), as well as on a SVM-based classifier acting on SWIR image differences.

Face Presentation Attack Detection

Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection

4 code implementations9 Jul 2019 Anjith George, Sebastien Marcel

The proposed approach achieves an HTER of 0% in Replay Mobile dataset and an ACER of 0. 42% in Protocol-1 of OULU dataset outperforming state of the art methods.

Face Anti-Spoofing Face Presentation Attack Detection +1

Domain Adaptation in Multi-Channel Autoencoder based Features for Robust Face Anti-Spoofing

1 code implementation9 Jul 2019 Olegs Nikisins, Anjith George, Sebastien Marcel

The proposed system is tested on a very recent publicly available multi-channel PAD database with a wide variety of presentation attacks.

Domain Adaptation Face Anti-Spoofing +2

DeepFakes: a New Threat to Face Recognition? Assessment and Detection

1 code implementation20 Dec 2018 Pavel Korshunov, Sebastien Marcel

The best performing method, which is based on visual quality metrics and is often used in presentation attack detection domain, resulted in 8. 97% equal error rate on high quality Deepfakes.

Constrained Lip-synchronization Face Recognition +1

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