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 …

Pre-trained vision-language models like CLIP have recently shown superior performances
on various downstream tasks, including image classification and segmentation. However, in …

Extracting robust feature representation is one of the key challenges in object re-
identification (ReID). Although convolution neural network (CNN)-based methods have …

Object re-identification (ReID) aims to find instances with the same identity as the given
probe from a large gallery. Pairwise losses play an important role in training a strong ReID …

General Instance Re-identification is a very important task in computer vision, which can be
widely used in many practical applications, such as person/vehicle re-identification, face …

Vehicle re-identification (Re-ID) is one of the promising applications in the field of computer
vision. Existing vehicle Re-ID methods mainly focus on global appearance features or pre …

Vision-based Automated Vehicle Recognition (VAVR) has attracted considerable attention
recently. Particularly given the reliance on emerging deep learning methods, which have …

Transformers are more and more popular in computer vision, which treat an image as a
sequence of patches and learn robust global features from the sequence. However, pure …

Person Re-IDentification (ReID) aims at re-identifying persons from different viewpoints
across multiple cameras. Capturing the fine-grained appearance differences is often the key …

Abstract Vehicle Re-Identification is to find images of the same vehicle from various views in
the cross-camera scenario. The main challenges of this task are the large intra-instance …