Pedestrian Attribute Recognition: A Survey

TL;DR

This survey reviews traditional and deep learning methods for pedestrian attribute recognition, discussing datasets, algorithms, challenges, and applications, and highlights future research directions in this important computer vision task.

Contribution

It provides a comprehensive overview of existing pedestrian attribute recognition techniques, including analysis of network architectures, learning algorithms, and application scenarios, with insights into future research directions.

Findings

Analysis of multi-task and multi-label learning in PAR

Review of popular deep learning architectures for PAR

Discussion of applications improving performance

Abstract

Recognizing pedestrian attributes is an important task in the computer vision community due to it plays an important role in video surveillance. Many algorithms have been proposed to handle this task. The goal of this paper is to review existing works using traditional methods or based on deep learning networks. Firstly, we introduce the background of pedestrian attribute recognition (PAR, for short), including the fundamental concepts of pedestrian attributes and corresponding challenges. Secondly, we introduce existing benchmarks, including popular datasets and evaluation criteria. Thirdly, we analyze the concept of multi-task learning and multi-label learning and also explain the relations between these two learning algorithms and pedestrian attribute recognition. We also review some popular network architectures which have been widely applied in the deep learning community. Fourthly, we analyze popular solutions for this task, such as attributes group, part-based, etc. Fifthly, we show some applications that take pedestrian attributes into consideration and achieve better performance. Finally, we summarize this paper and give several possible research directions for pedestrian attribute recognition. We continuously update the following GitHub to keep tracking the most cutting-edge related works on pedestrian attribute recognition~\url{https://github.com/wangxiao5791509/Pedestrian-Attribute-Recognition-Paper-List}