Submit

Login Login

Register Register

Home / Journals / CMC / Online First / doi:10.32604/cmc.2025.070683
Journal Menu
Special Issues
Table of Content

All issues

Online First

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

Open Access

ARTICLE

Improving Person Recognition for Single-Person-in-Photos: Intimacy in Photo Collections

Xiaoyi Duan, Tianqi Zou, Chenyang Wang, Yu Gu, Xiuying Li*
Department of Electronic and Communication Engineering, Beijing Electronic Science & Technology Institute, Beijing, 100070, China
* Corresponding Author: Xiuying Li. Email: email

Computers, Materials & Continua https://doi.org/10.32604/cmc.2025.070683

Received 21 July 2025; Accepted 21 October 2025; Published online 21 November 2025

Abstract

Person recognition in photo collections is a critical yet challenging task in computer vision. Previous studies have used social relationships within photo collections to address this issue. However, these methods often fail when performing single-person-in-photos recognition in photo collections, as they cannot rely on social connections for recognition. In this work, we discard social relationships and instead measure the relationships between photos to solve this problem. We designed a new model that includes a multi-parameter attention network for adaptively fusing visual features and a unified formula for measuring photo intimacy. This model effectively recognizes individuals in single photo within the collection. Due to outdated annotations and missing photos in the existing PIPA (Person in Photo Album) dataset, we manually re-annotated it and added approximately ten thousand photos of Asian individuals to address the underrepresentation issue. Our results on the re-annotated PIPA dataset are superior to previous studies in most cases, and experiments on the supplemented dataset further demonstrate the effectiveness of our method. We have made the PIPA dataset publicly available on Zenodo, with the DOI: (accessed on 15 October 2025).

Keywords

Deep learning; computer vision; person recognition; photo intimacy; PIPA dataset

  • 140

    View

  • 25

    Download

  • 0

    Like

Related articles
Copyright© 2025 Tech Science Press
© 1997-2025 TSP (Henderson, USA) unless otherwise stated

Share Link