Existing public face image datasets are strongly biased toward Caucasian faces, and other
races (eg, Latino) are significantly underrepresented. The models trained from such datasets …

We address the problem of cross-domain image retrieval, considering the following practical
application: given a user photo depicting a clothing image, our goal is to retrieve the same or …

Person re-identification is an important task in video surveillance systems. It can be formally
defined as establishing the correspondence between images of a person taken from …

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

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 …

Person re-identification has been widely studied due to its importance in surveillance and
forensics applications. In practice, gallery images are high-resolution (HR) while probe …

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 …

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 …

The success of DNNs has driven the extensive applications of person re-identification
(ReID) into a new era. However, whether ReID inherits the vulnerability of DNNs remains …

Learning semantic attributes for person re-identification and description-based person
search has gained increasing interest due to attributes' great potential as a pose and view …