Face Anti-Spoofing

10 papers with code · Computer Vision

Facial anti-spoofing is the task of preventing false facial verification by using a photo, video, mask or a different substitute for an authorized person’s face. Some examples of attacks:

  • Print attack: The attacker uses someone’s photo. The image is printed or displayed on a digital device.

  • Replay/video attack: A more sophisticated way to trick the system, which usually requires a looped video of a victim’s face. This approach ensures behaviour and facial movements to look more ‘natural’ compared to holding someone’s photo.

  • 3D mask attack: During this type of attack, a mask is used as the tool of choice for spoofing. It’s an even more sophisticated attack than playing a face video. In addition to natural facial movements, it enables ways to deceive some extra layers of protection such as depth sensors.

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Greatest papers with code

Improving Face Anti-Spoofing by 3D Virtual Synthesis

2 Jan 2019cleardusk/3DDFA

Specifically, we consider a printed photo as a flat surface and mesh it into a 3D object, which is then randomly bent and rotated in 3D space.

FACE ANTI-SPOOFING FACE RECOGNITION

A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing

CVPR 2019 SoftwareGift/FeatherNets_Face-Anti-spoofing-Attack-Detection-Challenge-CVPR2019

To facilitate face anti-spoofing research, we introduce a large-scale multi-modal dataset, namely CASIA-SURF, which is the largest publicly available dataset for face anti-spoofing in terms of both subjects and visual modalities.

FACE ANTI-SPOOFING FACE RECOGNITION

Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing

17 Jan 2019XgTu/GFA-CNN

Face anti-spoofing (a. k. a presentation attack detection) has drawn growing attention due to the high-security demand in face authentication systems.

DOMAIN ADAPTATION FACE ANTI-SPOOFING FACE RECOGNITION

Learn Convolutional Neural Network for Face Anti-Spoofing

24 Aug 2014mnikitin/Learn-Convolutional-Neural-Network-for-Face-Anti-Spoofing

Moreover, the nets trained using combined data from two datasets have less biases between two datasets.

FACE ANTI-SPOOFING

Generalized Presentation Attack Detection: a face anti-spoofing evaluation proposal

12 Apr 2019Gradiant/bob.paper.icb2019.gradgpad

Over the past few years, Presentation Attack Detection (PAD) has become a fundamental part of facial recognition systems.

FACE ANTI-SPOOFING

Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection

9 Jul 2019anjith2006/bob.paper.deep_pix_bis_pad.icb2019

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 FACE RECOGNITION

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

9 Jul 2019anjith2006/bob.paper.mcae.icb2019

Face PAD datasets are usually captured with RGB cameras, and have very limited number of both bona-fide samples and presentation attack instruments.

DOMAIN ADAPTATION FACE ANTI-SPOOFING FACE PRESENTATION ATTACK DETECTION FACE RECOGNITION

Biometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Network

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2019 anjith2006/bob.paper.mccnn.tifs2018

We also introduce the new Wide Multi-Channel presentation Attack (WMCA) database for face PAD which contains a wide variety of 2D and 3D presentation attacks for both impersonation and obfuscation attacks.

FACE ANTI-SPOOFING FACE PRESENTATION ATTACK DETECTION FACE RECOGNITION