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 …

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 …

Occupancy and behavior in buildings are considered to be key factors influencing energy
consumption. Residential areas contribute substantially to energy consumption in urban …

The rapid emergence of airborne platforms and imaging sensors are enabling new forms of
aerial surveillance due to their unprecedented advantages in scale, mobility, deployment …

As large language models (LLMs) become ubiquitous in our daily tasks and digital
interactions, associated privacy risks are increasingly in focus. While LLM privacy research …

Abstract Pedestrian Attribute Recognition (PAR) is a challenging task in intelligent video
surveillance. Two key challenges in PAR include complex alignment relations between …

The widespread use of smartphones and other low-cost equipment as recording devices,
the massive growth in bandwidth, and the ever-growing demand for new applications with …

This paper proposes the Attribute Saliency Network (ASNet), a deep learning model that
utilizes attribute and saliency map learning for person re-identification (re-ID) task. Many re …

行人属性识别旨在判断目标行人的预定义属性标签, 从而生成关于该行人的结构化描述,
包括年龄, 性别, 衣着, 配饰等多种层次的语义信息. 由于行人属性识别在视频监控领域具有极大 …

The objective of pedestrian attribute recognition (PAR) is to recognize human attributes
based on the appearance of pedestrians in images. The PAR is a challenging task in video …