ML Anthology

A Multi-Task Convolutional Neural Network for Joint Iris Detection and Presentation Attack Detection

Cunjian Chen, Arun Ross
WACVW 2018 pp. 44-51
doi:10.1109/WACVW.2018.00011 /wacvw/2018/chen2018wacvw-multitask/

Abstract

In this work, we propose a multi-task convolutional neural network learning approach that can simultaneously perform iris localization and presentation attack detection (PAD). The proposed multi-task PAD (MT-PAD) is inspired by an object detection method which directly regresses the parameters of the iris bounding box and computes the probability of presentation attack from the input ocular image. Experiments involving both intra-sensor and cross-sensor scenarios suggest that the proposed method can achieve state-of-the-art results on publicly available datasets. To the best of our knowledge, this is the first work that performs iris detection and iris presentation attack detection simultaneously.

WACVW Semantic Scholar

Cite

Text

Chen and Ross. "A Multi-Task Convolutional Neural Network for Joint Iris Detection and Presentation Attack Detection." IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2018. doi:10.1109/WACVW.2018.00011

Markdown

[Chen and Ross. "A Multi-Task Convolutional Neural Network for Joint Iris Detection and Presentation Attack Detection." IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2018.](https://mlanthology.org/wacvw/2018/chen2018wacvw-multitask/) doi:10.1109/WACVW.2018.00011

BibTeX

@inproceedings{chen2018wacvw-multitask,
  title     = {{A Multi-Task Convolutional Neural Network for Joint Iris Detection and Presentation Attack Detection}},
  author    = {Chen, Cunjian and Ross, Arun},
  booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision Workshops},
  year      = {2018},
  pages     = {44-51},
  doi       = {10.1109/WACVW.2018.00011},
  url       = {https://mlanthology.org/wacvw/2018/chen2018wacvw-multitask/}
}