Awesome Person Re-identification

Implementing RepNet(a two-stream multitask learning network) to do vehicle Re-identification, vehicle search(or vehicle match) with PyTorch 可用于车辆细粒度识别，车辆再识别，车辆匹配，车辆检索，RepNet/MDNet的一种PyTorch实现

The 3rd Place Submission to AICity Challenge 2020 Track2

Annotations of key point location and vehicle orientation for VeRi-776 dataset. ICCV'17 paper: Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-identification.

VehicleX: Simulating Content Consistent Vehicle Datasets with Attribute Descent (ECCV 2020, TPAMI 2023)

Awesome Vehicle Re-identification

Vehicle-Rear: A New Dataset to Explore Feature Fusion For Vehicle Identification Using Convolutional Neural Networks

【CVPR2024】Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification

code for ICCV19 paper "Deep Meta Metric Learning"

Welcome to the Awesome Multi-Modal Object Re-Identification Repository! This repository is dedicated to curating and sharing the latest methods, datasets, and resources focused specifically on the domain of multi-modal object re-identification. It brings together cutting-edge research, tools, and papers aimed at advancing the study and application.

Vehicle Re-identification

Code for Part-Guided Attention Learning for Vehicle Instance Retrieval (TITS2020). A strong Vehicle Re-ID model with part region guidance.

Semantics-guided Part Attention Network (ECCV 2020 Oral)

Vehicle Re-Identification (ReID) dataset contains over 55,000 images for training and validation of the vehicle re-identification model

V2ReID: Vision-Outlooker-Based Vehicle Re-Identification

UC3M Vehicle Re-Identification dataset

In this project, a novel framework is used from the reference mentioned in the README, which successfully encodes both geometric local features and global representations to distinguish vehicle instances, optimized only by the supervision from official ID labels. Specifically, given the insight that objects in ReID share similar geometric characteristics, a self-supervised representation learning technique is used to facilitate geometric features discovery. To condense these features, an interpretable attention module, with the core of local maxima aggregation instead of fully automatic learning, in used, whose mechanism is completely understandable and whose response map is physically reasonable.

A Python-based system leveraging YOLO for vehicle detection and re-identification in images and videos. Designed for traffic analysis, surveillance, and smart city applications, it enables robust vehicle tracking and recognition across multiple camera views.

A Streamlit-based web application designed for Vehicle Re-Identification (Re-ID) tasks.

This repository contains the LaTeX source files for my Master's thesis on Vehicle Re-Identification. It includes the main .tex document, bibliography, figures, and any supplementary materials used in the thesis compilation.