In this paper, a novel knowledge distillation (KD)-based pedestrian attribute recognition
(PAR) model is developed, where a multi-label mixed feature learning network (MMFL-Net) …

Searching techniques in most of existing neural architecture search (NAS) algorithms are
mainly dominated by differentiable methods for the efficiency reason. In contrast, we develop …

Person re-identification is a challenging task due to various complex factors. Recent studies
have attempted to integrate human parsing results or externally defined attributes to help …

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 …

In this paper, we propose a new end-to-end network, named Joint Learning of Attribute and
Contextual relations (JLAC), to solve the task of pedestrian attribute recognition. It includes …

Pedestrian attribute recognition (PAR), which aims to identify attributes of the pedestrians
captured in video surveillance, is a challenging task due to the poor quality of images and …

Pedestrian attribute recognition aims to assign multiple attributes to one pedestrian image
captured by a video surveillance camera. Although numerous methods are proposed and …

Although various methods have been proposed for pedestrian attribute recognition, most
studies follow the same feature learning mechanism,\ie, learning a shared pedestrian image …

Binary neural networks have attracted tremendous attention due to the efficiency for
deploying them on mobile devices. Since the weak expression ability of binary weights and …

Pedestrian attribute recognition (PAR) has received increasing attention because of its wide
application in video surveillance and pedestrian analysis. Extracting robust feature …