Human-centric visual tasks have attracted increasing research attention due to their
widespread applications. In this paper, we aim to learn a general human representation from …

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) …

In the post-deep learning era, the Transformer architecture has demonstrated its powerful
performance across pre-trained big models and various downstream tasks. However, the …

Long-tailed data distribution is common in many multi-label visual recognition tasks and the
direct use of these data for training usually leads to relatively low performance on tail …

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 …

Relational reasoning is at the heart of video question answering. However, existing
approaches suffer from several common limitations:(1) they only focus on either object-level …

Recognizing soft-biometric pedestrian attributes is essential in video surveillance and
fashion retrieval. Recent works show promising results on single datasets. Nevertheless, the …

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

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