In this paper, we discuss input/output architectures for convolutional neural network (CNN)-
based cross-view gait recognition. For this purpose, we consider two aspects: verification …

In this paper, we propose a pairwise spatial transformer network (PSTN) for cross-view gait
recognition, which reduces unwanted feature mis-alignment due to view differences before a …

Recently, deep learning-based cross-view gait recognition has become popular owing to the
strong capacity of convolutional neural networks (CNNs). Current deep learning methods …

Gait benchmarks empower the research community to train and evaluate high-performance
gait recognition systems. Even though growing efforts have been devoted to cross-view …

Human gait recognition has a wide range of applications in multiple fields, such as video
surveillance, digital security, and forensics. In this paper, we investigate the challenging …

Gait recognition is an important yet challenging problem in computer vision. The changing
view of gait is one of the most challenging factors, which could greatly affect the accuracy of …

Gait recognition aims to recognize persons' identities by walking styles. Gait recognition has
unique advantages due to its characteristics of non-contact and long-distance compared …

Gait recognition can be used in person identification and re-identification by itself or in
conjunction with other biometrics. Although gait has both spatial and temporal attributes, and …

Gait can be used to recognize people in an uncooperative and noninvasive manner and it is
hard to imitate or counterfeit, which makes it suitable for video surveillance. The current …

This paper describes the world's largest gait database with wide view variation, the “OU-ISIR
gait database, multi-view large population dataset (OU-MVLP)”, and its application to a …