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

Showing 110 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-identification0
UCM-VeID V2: A Richer Dataset and A Pre-training Method for UAV Cross-Modality Vehicle Re-Identification0
Adaptive Aspect Ratios with Patch-Mixup-ViT-based Vehicle ReIDCode0
Revisiting Multi-Granularity Representation via Group Contrastive Learning for Unsupervised Vehicle Re-identification0
Multimodality Adaptive Transformer and Mutual Learning for Unsupervised Domain Adaptation Vehicle Re-Identification0
UAV (Unmanned Aerial Vehicles): Diverse Applications of UAV Datasets in Segmentation, Classification, Detection, and Tracking0
Optimizing ROI Benefits Vehicle ReID in ITS0
Study on Aspect Ratio Variability toward Robustness of Vision Transformer-based Vehicle Re-identification0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Recall@k Surrogate loss (ViT-B/16)Rank-195.2Unverified
2Recall@k Surrogate loss (ResNet-50)Rank-194.6Unverified
3PNP LossRank-194.2Unverified
4RPTMRank-193.3Unverified
5Smooth-APRank-193.3Unverified
6ANetRank-182.8Unverified
7vehiclenetRank-181.35Unverified
8CALRank-178.2Unverified
9QD-DLFmAP74.63Unverified