Improving Face Anti-Spoofing by 3D Virtual Synthesis

Published in

International Conference on Biometrics(2019)

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TL;DR

A method to synthesize virtual spoof data in 3D space to alleviate the problem of expensive spoof data acquisition and open up new possibilities for advancing face anti-spoofing using cheap and large-scale synthetic data.

Abstract

Face anti-spoofing is crucial for the security of face recognition systems. Learning based methods especially deep learning based methods need large-scale training samples to reduce overfitting. However, acquiring spoof data is very expensive since the live faces should be reprinted and re-captured in many views. In this paper, we present a method to synthesize virtual spoof data in 3D space to alleviate this problem. 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. Afterward, the transformed 3D photo is rendered through perspective projection as a virtual sample. The synthetic virtual samples can significantly boost the anti-spoofing performance when combined with a proposed data balancing strategy. Our promising results open up new possibilities for advancing face anti-spoofing using cheap and large-scale synthetic data.

Authors

Zhen Lei

13 papers

S. Li

18 papers

Xiangyu Zhu

7 papers

References45 items

Exploiting temporal and depth information for multi-frame face anti-spoofing

On the Learning of Deep Local Features for Robust Face Spoofing Detection

Face Synthesis for Eyeglass-Robust Face Recognition

A Performance Evaluation of Convolutional Neural Networks for Face Anti Spoofing

Dominant and Complementary Emotion Recognition From Still Images of Faces

Improving Face Anti-Spoofing by 3D Virtual Synthesis

Published in

International Conference on Biometrics(2019)

External Links:

Generate Graph DownloadPDF

TL;DR

Abstract

Authors

Zhen Lei

13 papers

S. Li

18 papers

Xiangyu Zhu

7 papers

References45 items

Exploiting temporal and depth information for multi-frame face anti-spoofing

On the Learning of Deep Local Features for Robust Face Spoofing Detection

Face Synthesis for Eyeglass-Robust Face Recognition

A Performance Evaluation of Convolutional Neural Networks for Face Anti Spoofing

Dominant and Complementary Emotion Recognition From Still Images of Faces

Jianzhu Guo

3 papers

Jinchuan Xiao

1 papers

TL;DR

Abstract

Authors

References45 items

Exploiting temporal and depth information for multi-frame face anti-spoofing

On the Learning of Deep Local Features for Robust Face Spoofing Detection

Face Synthesis for Eyeglass-Robust Face Recognition

A Performance Evaluation of Convolutional Neural Networks for Face Anti Spoofing

Dominant and Complementary Emotion Recognition From Still Images of Faces

TL;DR

Abstract

Authors

References45 items

Exploiting temporal and depth information for multi-frame face anti-spoofing

On the Learning of Deep Local Features for Robust Face Spoofing Detection

Face Synthesis for Eyeglass-Robust Face Recognition

A Performance Evaluation of Convolutional Neural Networks for Face Anti Spoofing

Dominant and Complementary Emotion Recognition From Still Images of Faces

Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision

Face anti-spoofing using patch and depth-based CNNs

Countermeasures to face photo spoofing attacks by exploiting structure and texture information from rotated face sequences

Transfer Learning Using Convolutional Neural Networks for Face Anti-spoofing

OULU-NPU: A Mobile Face Presentation Attack Database with Real-World Variations

Multi-modality Network with Visual and Geometrical Information for Micro Emotion Recognition

3D Convolutional Neural Network Based on Face Anti-spoofing

Face Antispoofing Using Speeded-Up Robust Features and Fisher Vector Encoding

An original face anti-spoofing approach using partial convolutional neural network

Face anti-spoofing with multifeature videolet aggregation

Cross-Database Face Antispoofing with Robust Feature Representation

Marker-Less 3D Human Motion Capture with Monocular Image Sequence and Height-Maps

Learning Camera Viewpoint Using CNN to Improve 3D Body Pose Estimation

MoCap-guided Data Augmentation for 3D Pose Estimation in the Wild

Integration of image quality and motion cues for face anti-spoofing: A neural network approach

3D Action Recognition from Novel Viewpoints

Synthesizing Training Images for Boosting Human 3D Pose Estimation

Deep Residual Learning for Image Recognition

Deep Exemplar 2D-3D Detection by Adapting from Real to Rendered Views

The MegaFace Benchmark: 1 Million Faces for Recognition at Scale

Face Alignment in Full Pose Range: A 3D Total Solution

Face anti-spoofing based on color texture analysis

Learning temporal features using LSTM-CNN architecture for face anti-spoofing

Learning a non-linear knowledge transfer model for cross-view action recognition

Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views

Live face video vs. spoof face video: Use of moiré patterns to detect replay video attacks

Learn Convolutional Neural Network for Face Anti-Spoofing

Context based face anti-spoofing

Can face anti-spoofing countermeasures work in a real world scenario?

Face liveness detection with component dependent descriptor

On the effectiveness of local binary patterns in face anti-spoofing

A face antispoofing database with diverse attacks

Articulated people detection and pose estimation: Reshaping the future

Learning people detection models from few training samples

Face recognition in unconstrained videos with matched background similarity

Multi-view object class detection with a 3D geometric model

Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments

Multi-PIE

Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera

LBP − T OP based countermeasure against face spooﬁng attacks

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