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Age-Invariant Face Recognition by Multi-Feature Fusionand Decomposition with Self-attention

Authors:

Bolun ZhengAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 18, Issue 1s

Article No.: 29, Pages 1 - 18

https://doi.org/10.1145/3472810

Published: 25 January 2022 Publication History

Abstract

Different from general face recognition, age-invariant face recognition (AIFR) aims at matching faces with a big age gap. Previous discriminative methods usually focus on decomposing facial feature into age-related and age-invariant components, which suffer from the loss of facial identity information. In this article, we propose a novel Multi-feature Fusion and Decomposition (MFD) framework for age-invariant face recognition, which learns more discriminative and robust features and reduces the intra-class variants. Specifically, we first sample multiple face images of different ages with the same identity as a face time sequence. Then, the multi-head attention is employed to capture contextual information from facial feature series, extracted by the backbone network. Next, we combine feature decomposition with fusion based on the face time sequence to ensure that the final age-independent features effectively represent the identity information of the face and have stronger robustness against the aging process. Besides, we also mitigate imbalanced age distribution in the training data by a re-weighted age loss. We experimented with the proposed MFD over the popular CACD and CACD-VS datasets, where we show that our approach improves the AIFR performance than previous state-of-the-art methods. We simultaneously show the performance of MFD on LFW dataset.

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Index Terms

Age-Invariant Face Recognition by Multi-Feature Fusionand Decomposition with Self-attention
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision representations
        Appearance and texture representations

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cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 18, Issue 1s

February 2022

352 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3505206

Editor:
Alberto Del Bimbo
University of Firenze, Italy

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Publication History

Published: 25 January 2022

Accepted: 01 June 2021

Revised: 01 May 2021

Received: 01 January 2021

Published in TOMM Volume 18, Issue 1s

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National Key Research and Development Program of China
National Natural Science Foundation of China
Zhejiang Province Natural Science Foundation of China
Youth Innovation Promotion Association of Chinese Academy of Sciences
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