SOTAVerified

Vehicle Re-Identification

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 )

Papers

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Showing 1–10 of 150 papers

TitleStatusHype
CORE-ReID V2: Advancing the Domain Adaptation for Object Re-Identification with Optimized Training and Ensemble FusionCode0
Collaborative Enhancement Network for Low-quality Multi-spectral Vehicle Re-identificationCode0
CLIP-SENet: CLIP-based Semantic Enhancement Network for Vehicle Re-identification—0
UCM-VeID V2: A Richer Dataset and A Pre-training Method for UAV Cross-Modality Vehicle Re-Identification—0
Adaptive Aspect Ratios with Patch-Mixup-ViT-based Vehicle ReIDCode0
Revisiting Multi-Granularity Representation via Group Contrastive Learning for Unsupervised Vehicle Re-identification—0
Multimodality Adaptive Transformer and Mutual Learning for Unsupervised Domain Adaptation Vehicle Re-Identification—0
UAV (Unmanned Aerial Vehicles): Diverse Applications of UAV Datasets in Segmentation, Classification, Detection, and Tracking—0
Optimizing ROI Benefits Vehicle ReID in ITS—0
Study on Aspect Ratio Variability toward Robustness of Vision Transformer-based Vehicle Re-identification—0
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All datasetsVeRi-776VehicleID SmallVehicleID LargeVehicleID MediumVRAI test-devVeRi-Wild SmallVRAI testVeRiVeRi-Wild LargeCityFlowVehicleIDVeRi-Wild Medium

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1A Strong BaselinemAP61.34—Unverified