Person re-identification (Re-ID) technology plays an increasingly crucial role in intelligent
surveillance systems. Widespread occlusion significantly impacts the performance of person …

Abstract Object Re-identification (Re-ID) aims to identify specific objects across different
times and scenes, which is a widely researched task in computer vision. For a prolonged …

Person Re-identification (ReID) plays a more and more crucial role in recent years with a
wide range of applications. Existing ReID methods are suffering from the challenges of …

Although recent studies empirically show that injecting Convolutional Neural Networks
(CNNs) into Vision Transformers (ViTs) can improve the performance of person re …

A proposed method, Enhancement, integration, and Expansion, aims to activate the
representation of detailed features for occluded person re-identification. Region and context …

Recent development in computing power has resulted in performance improvements on
holistic (none-occluded) person Re-Identification (ReID) tasks. Nevertheless, the precision …

Text-based person search aims to retrieve the specified person images given a textual
description. The key to tackling such a challenging task is to learn powerful multi-modal …

Re-identification (ReID) of occluded persons is a challenging task due to the loss of
information in scenes with occlusions. Most existing methods for occluded ReID use 2D …

In person re-identification (ReID) task, it is still challenging to learn discriminative
representation by deep learning, due to limited data. Generally speaking, the model will get …

This paper proposes a Semi-Attention Partition (SAP) method to learn well-aligned part
features for occluded person re-identification (re-ID). Currently, the mainstream methods …