On Attribute Aware Open-Set Face Verification

Arun Subramanian, Anoop Namboodiri

2023

Abstract

Deep Learning on face recognition problems has shown extremely high accuracy owing to their ability in finding strongly discriminating features. However, face images in the wild show variations in pose, lighting, expressions, and the presence of facial attributes (for example eyeglasses). We ask, why then are these variations not detected and used during the matching process? We demonstrate that this is indeed possible while restricting ourselves to facial attribute variation, to prove the case in point. We show two ways of doing so. a) By using the face attribute labels as a form of prior, we bin the matching template pairs into three bins depending on whether each template of the matching pair possesses a given facial attribute or not. By operating on each bin and averaging the result, we better the EER of SOTA by over 1 % over a large set of matching pairs. b) We use the attribute labels and correlate them with each neuron of an embedding generated by a SOTA architecture pre-trained DNN on a large Face dataset and fine-tuned on face-attribute labels. We then suppress a set of maximally correlating neurons and perform matching after doing so. We demonstrate this improves the EER by over 2 %.

Paper Citation

in Harvard Style

Subramanian A. and Namboodiri A. (2023). On Attribute Aware Open-Set Face Verification. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP; ISBN 978-989-758-634-7, SciTePress, pages 161-172. DOI: 10.5220/0011687000003417

in Bibtex Style

@conference{visapp23,
author={Arun Subramanian and Anoop Namboodiri},
title={On Attribute Aware Open-Set Face Verification},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP},
year={2023},
pages={161-172},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011687000003417},
isbn={978-989-758-634-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP
TI - On Attribute Aware Open-Set Face Verification
SN - 978-989-758-634-7
AU - Subramanian A.
AU - Namboodiri A.
PY - 2023
SP - 161
EP - 172
DO - 10.5220/0011687000003417
PB - SciTePress