A Multi-Task Comparator Framework for Kinship Verification

• URL: http://arxiv.org/abs/2006.01615v1
• Date: Tue, 2 Jun 2020 14:00:09 GMT
• Title: A Multi-Task Comparator Framework for Kinship Verification
• Authors: Stefan H\"ormann, Martin Knoche, Gerhard Rigoll
• Abstract summary: kinship verification often relies on cosine distances between face identification features. Gender bias inherent in these features makes it hard to reliably predict whether two opposite-gender pairs are related. We show that our framework is robust against this gender bias and achieves comparable results on two tracks of the RFIW Challenge 2020.
• Score: 5.908471365011942
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Approaches for kinship verification often rely on cosine distances between face identification features. However, due to gender bias inherent in these features, it is hard to reliably predict whether two opposite-gender pairs are related. Instead of fine tuning the feature extractor network on kinship verification, we propose a comparator network to cope with this bias. After concatenating both features, cascaded local expert networks extract the information most relevant for their corresponding kinship relation. We demonstrate that our framework is robust against this gender bias and achieves comparable results on two tracks of the RFIW Challenge 2020. Moreover, we show how our framework can be further extended to handle partially known or unknown kinship relations.

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