ImagesVideosHyperspectral imagesRGB-D

HQ-WMCA

High-Quality Wide Multi-Channel Attack database

Introduced in Deep Models and Shortwave Infrared Information to Detect Face Presentation Attacks2020

About this Dataset

The High-Quality Wide Multi-Channel Attack database (HQ-WMCA) database consists of 2904 short multi-modal video recordings of both bona-fide and presentation attacks. There are 555 bonafide presentations from 51 participants and the remaining 2349 are presentation attacks. The data is recorded from several channels including color, depth, thermal, infrared (spectra), and short-wave infrared (spectra).

Source: Deep Models and Shortwave Infrared Information to Detect Face Presentation Attacks

Dataset Variants

HQ-WMCA

Papers1

Deep Models and Shortwave Infrared Information to Detect Face Presentation Attacks

The best proposed approach is able to almost perfectly detect all impersonation attacks while ensuring low bonafide classification errors, and obtained results show that obfuscation attacks are more difficult to detect.

Tasks

EDIT

Face Anti-Spoofing

Similar Datasets

MNIST

CelebA

JFT-300M

Statistics

Papers

1

Tasks

128

Introduced

2020

Modalities

ImagesVideosHyperspectral imagesRGB-D

Languages

English