The capability of recognizing pedestrian attributes, such as gender and clothing style, at far
distance, is of practical interest in far-view surveillance scenarios where face and body close …

In real video surveillance scenarios, visual pedestrian attributes, such as gender, backpack,
clothes types, are very important for pedestrian retrieval and person reidentification. Existing …

Pedestrian attribute recognition has been an emerging research topic in the area of video
surveillance. To predict the existence of a particular attribute, it is demanded to localize the …

Retrieving specific persons with various types of queries, eg, a set of attributes or a portrait
photo has great application potential in large-scale intelligent surveillance systems. In this …

We address the problem of describing people based on fine-grained clothing attributes. This
is an important problem for many practical applications, such as identifying target suspects …

While recent studies on pedestrian attribute recognition have shown remarkable progress in
leveraging complicated networks and attention mechanisms, most of them neglect the inter …

This paper presents fine-tuned CNN features for person re-identification. Recently, features
extracted from top layers of pre-trained Convolutional Neural Network (CNN) on a large …

In this paper, we aim to improve the dataset foundation for pedestrian attribute recognition in
real surveillance scenarios. Recognition of human attributes, such as gender, and clothes …

Recognizing pedestrian attributes, such as gender, backpack, and cloth types, has obtained
increasing attention recently due to its great potential in intelligent video surveillance …

Abstract Pedestrian Attribute Recognition (PAR) is an important task in computer vision
community and plays an important role in practical video surveillance. The goal of this paper …