Vehicle Re-Identification
53 papers with code • 12 benchmarks • 9 datasets
Vehicle re-identification is the task of identifying the same vehicle across multiple cameras.
( Image credit: A Two-Stream Siamese Neural Network for Vehicle Re-Identification by Using Non-Overlapping Cameras )
Benchmarks
These leaderboards are used to track progress in Vehicle Re-Identification
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Libraries
Use these libraries to find Vehicle Re-Identification models and implementationsDatasets
VehicleID
VeRi-776
CityFlow
VeRi-Wild
VehicleX
VRAI
Vehicle-Rear
Vehicle-1M
Car datasets in multiple scenes
Latest papers
Multi‑camera trajectory matching based on hierarchical clustering and constraints
regob/vehicle_mtmc
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Multimedia Tools and Applications 2023
The fast improvement of deep learning methods resulted in breakthroughs in image classification, object detection, and object tracking.
Strength in Diversity: Multi-Branch Representation Learning for Vehicle Re-Identification
videturfortuna/vehicle_reid_itsc2023
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A lightweight solution using grouped convolution is also proposed to mimic the learning of loss-splitting into multiple embeddings while significantly reducing the model size.
Flare-Aware Cross-modal Enhancement Network for Multi-spectral Vehicle Re-identification
Finally, to evaluate the proposed FACENet in handling intense flare, we introduce a new multi-spectral vehicle re-ID dataset, called WMVEID863, with additional challenges such as motion blur, significant background changes, and particularly intense flare degradation.
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID
Neural Architecture Search (NAS) has been increasingly appealing to the society of object Re-Identification (ReID), for that task-specific architectures significantly improve the retrieval performance.
SIVD: Dataset of Iranian Vehicles for Real-Time Multi-Camera Video Tracking and Recognition
Farbod-Siahkali/Iranian-Vehicle-Tracking-and-Recognition
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ICSPIS 2023
Therefore, for the purposes of this paper, Iranian vehicle images from car sales websites are collected, and the SIVD dataset is proposed which contains 29 classes and 36, 705 images.
Self-supervised Geometric Features Discovery via Interpretable Attentio for Vehicle Re-Identification and Beyond (Complete Version)
ming1993li/self-supervised-geometric
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To learn distinguishable patterns, most of recent works in vehicle re-identification (ReID) struggled to redevelop official benchmarks to provide various supervisions, which requires prohibitive human labors.
Triplet Contrastive Representation Learning for Unsupervised Vehicle Re-identification
To address this problem, in this paper, we propose a simple Triplet Contrastive Representation Learning (TCRL) framework which leverages cluster features to bridge the part features and global features for unsupervised vehicle re-identification.
CLIP-ReID: Exploiting Vision-Language Model for Image Re-Identification without Concrete Text Labels
The key idea is to fully exploit the cross-modal description ability in CLIP through a set of learnable text tokens for each ID and give them to the text encoder to form ambiguous descriptions.
Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification
Lifelong object re-identification incrementally learns from a stream of re-identification tasks.
Synthehicle: Multi-Vehicle Multi-Camera Tracking in Virtual Cities
Smart City applications such as intelligent traffic routing or accident prevention rely on computer vision methods for exact vehicle localization and tracking.
