IEICE Technical Committee Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2022-12-16 15:55
Improving Pedestrian Attribute Recognition with Spatial Attention and Attribute Correlation
Yichen Chen, Tetsuya Matsumoto (Nagoya Univ.), Yoshinori Takeuchi (Daido Univ.), Hiroaki Kudo (Nagoya Univ.) IMQ2022-18
Abstract (in Japanese) (See Japanese page) 
(in English) In the field of video surveillance, pedestrian attribute recognition is a focus technical thema of study. To predict certain attributes of a pedestrian, it is necessary to localize areas associated with such attributes from an image since region annotations for this task are unavailable. Previous methods try that they introduce heuristic body-part localization processes to improve local feature representations. However, they didn't use attributes to define local feature regions. In addition, correlations between attributes have not been utilized. In real-world video surveillance scenarios, visual pedestrian attributes such as gender, clothing color, and so on, are crucial for pedestrian attribute recognition. According to the correlation of attributes, it is considered useful to localize the regions. In this report, we propose an attribute estimation network from pedestrians based on spatial attention maps and attribute correlations. Spatial attention can help the network focus on where each attribute should be concerned, and the correlation between attributes helps to reduce some incorrect predictions. In the experiments using pedestrian attribute datasets, we obtained the results that the proposed method estimates binary attributes with roughly 90% accuracy and categorical attributes with around 75% accuracy. For the mA and F1 metrics, the Attribute correlation attention module can enhance performance by 1.36% and 1.57%, respectively. The Spatial attention module can also improve performance by 0.57% and 0.67%.
Keyword (in Japanese) (See Japanese page) 
(in English) video surveillance / pedestrian attribute recognition / spatial attention / attributes correlation / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 317, IMQ2022-18, pp. 16-21, Dec. 2022.
Paper # IMQ2022-18 
Date of Issue 2022-12-09 (IMQ) 
ISSN Online edition: ISSN 2432-6380
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF IMQ2022-18

Conference Information
Committee IMQ  
Conference Date 2022-12-16 - 2022-12-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Nishi-Chiba Campus, Chiba Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Media Quality, etc. 
Paper Information
Registration To IMQ 
Conference Code 2022-12-IMQ 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Improving Pedestrian Attribute Recognition with Spatial Attention and Attribute Correlation 
Sub Title (in English)  
Keyword(1) video surveillance  
Keyword(2) pedestrian attribute recognition  
Keyword(3) spatial attention  
Keyword(4) attributes correlation  
1st Author's Name Yichen Chen  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Tetsuya Matsumoto  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Yoshinori Takeuchi  
3rd Author's Affiliation Daido University (Daido Univ.)
4th Author's Name Hiroaki Kudo  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
Speaker Author-1 
Date Time 2022-12-16 15:55:00 
Presentation Time 25 minutes 
Registration for IMQ 
Paper # IMQ2022-18 
Volume (vol) vol.122 
Number (no) no.317 
Page pp.16-21 
Date of Issue 2022-12-09 (IMQ) 

[Return to Top Page]

[Return to IEICE Web Page]

The Institute of Electronics, Information and Communication Engineers (IEICE), Japan