Pedestrian Attribute Recognition: A Survey

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}

arXiv commentCheck the most recent works on PAR on our Github: https://github.com/wangxiao5791509/Pedestrian-Attribute-Recognition-Paper-List

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Cited by in corpus (10)

• Levels of explainable artificial intelligence for human-aligned conversational explanations
• Attributes Guided Feature Learning for Vehicle Re-identification
• Improving Pedestrian Attribute Recognition With Weakly-Supervised Multi-Scale Attribute-Specific Localization
• Deep Template Matching for Pedestrian Attribute Recognition with the Auxiliary Supervision of Attribute-wise Keypoints
• Large-Scale Attribute-Object Compositions
• Improved Hard Example Mining by Discovering Attribute-based Hard Person Identity
• STADB: A Self-Thresholding Attention Guided ADB Network for Person Re-identification
• FashionSearchNet-v2: Learning Attribute Representations with Localization for Image Retrieval with Attribute Manipulation
• Robust Pedestrian Attribute Recognition Using Group Sparsity for Occlusion Videos
• Can Human Sex Be Learned Using Only 2D Body Keypoint Estimations?