There are 6 repositories under vehicle-reid topic.
:bouncing_ball_person: Pytorch ReID: A tiny, friendly, strong pytorch implement of person re-id / vehicle re-id baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial
Awesome Person Re-identification
:red_car: the collection of vehicle re-ID papers, datasets. :red_car:
:red_car: The 1st Place Submission to AICity Challenge 2020 re-id track (Baidu-UTS submission)
Reimplementation of Bag of Tricks and A Strong Baseline for Deep Person Re-identification
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
OpenVINO Training Extensions Object Re-identification
This repo gives the code for the paper "Xinchen Liu, Wu Liu, Jinkai Zheng, Chenggang Yan, Tao Mei: Beyond the Parts: Learning Multi-view Cross-part Correlation for Vehicle Re-identification. ACM MM 2020".
【AAAI2024】TOP-ReID: Multi-spectral Object Re-Identification with Token Permutation
Code for Part-Guided Attention Learning for Vehicle Instance Retrieval (TITS2020). A strong Vehicle Re-ID model with part region guidance.
Repository for 2019 CVPR AI City Challenge Track 2 from IPL@UW
AICITY2020 track2 reid open source code.
Vehicle Re-identification
:fire: The runner-up solution of AICITY Challenge Track2 (Vehicle Re-Identification) at CVPR 2021 Workshop.
vehicle-reid-0001 を用いて、Vehicle ReIDを行うサンプル
Vehicle Re-Identification (ReID) dataset contains over 55,000 images for training and validation of the vehicle re-identification model
Vehicle counting and tracking at intersection modules and ReID pipeline with object detection - > image cropping -> object in cropped image re-identification in another image
Training a customized dataset on fast-reid, evaluation and visualization