In video surveillance, pedestrian retrieval (also called person reidentification) is a critical
task. This task aims to retrieve the pedestrian of interest from nonoverlapping cameras …

Nowadays, there are many video person re-identification networks that do not consider
screening the input video frame sequence, which result in the high-similarity of the video …

To automatically mine structured semantic topics from text, neural topic modeling has arisen
and made some progress. However, most existing work focuses on designing a mechanism …

Person re-identification refers to the process of recognizing a person across several non-
overlapping cameras. It is becoming increasingly important in computer vision for real-world …

With rich temporal-spatial information, video-based person re-identification methods have
shown broad prospects. Although tracklets can be easily obtained with ready-made tracking …

Currently, supervised person re-identification (Re-ID) models trained on labeled datasets
can achieve high recognition performance in the same data domain. However, accuracy …

Supervised person re-identification methods rely heavily on high-quality cross-camera
training label. This significantly hinders the deployment of re-ID models in real-world …

The superior performances of pre-trained vision-language models on various downstream
tasks demonstrate the effectiveness of integrating cross-modal vision-language knowledge …

行人重识别旨在跨监控摄像头下检索出特定的行人目标. 由于存在姿态变化,
物体遮挡和背景干扰的不同成像条件等问题, 导致行人特征提取不充分. 本文提出一种利用多核 …

Although deep learning-based point cloud technologies have achieved significant progress
during the past decade, lots of further investigations are still needed due to opportunities …