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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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 41–50 of 150 papers

Title	Date	Tasks	Status	Hype
Context-Aware Graph Convolution Network for Target Re-identification	Dec 8, 2020	Vehicle Re-Identification	—Unverified	0
A unified neural network for object detection, multiple object tracking and vehicle re-identification	Jul 8, 2019	Multiple Object TrackingObject	—Unverified	0
Complete Solution for Vehicle Re-ID in Surround-view Camera System	Dec 8, 2022	Autonomous DrivingVehicle Re-Identification	—Unverified	0
Image-based Vehicle Re-identification Model with Adaptive Attention Modules and Metadata Re-ranking	Jul 3, 2020	Re-RankingVehicle Re-Identification	—Unverified	0
Image-to-image domain adaptation for vehicle re-identification	Mar 30, 2023	Domain AdaptationGenerative Adversarial Network	—Unverified	0
Attributes Guided Feature Learning for Vehicle Re-identification	May 22, 2019	Generative Adversarial NetworkVehicle Re-Identification	—Unverified	0
Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification	Dec 11, 2018	Vehicle Re-Identification	—Unverified	0
A Novel Dual-pooling Attention Module for UAV Vehicle Re-identification	Jun 25, 2023	Single Particle AnalysisTriplet	—Unverified	0
Enhanced Vehicle Re-identification for ITS: A Feature Fusion approach using Deep Learning	Aug 13, 2022	Vehicle Re-Identification	—Unverified	0
Cluster images with AntClust: a clustering algorithm based on the chemical recognition system of ants	Dec 8, 2023	ClusteringVehicle Re-Identification	—Unverified	0

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All datasets VeRi-776 VehicleID Small VehicleID Large VehicleID Medium VRAI test-dev VeRi-Wild Small VRAI test VeRi VeRi-Wild Large CityFlow VehicleID VeRi-Wild Medium

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MBR4B-LAI (w/ RK)	mAP	92.1	—	Unverified
2	RPTM	mAP	88	—	Unverified
3	A Strong Baseline	mAP	87.1	—	Unverified
4	MBR4B-LAI (without re-ranking)	mAP	86	—	Unverified
5	MBR4B (without re-ranking)	mAP	84.72	—	Unverified
6	CLIP-ReID (without re-ranking)	mAP	84.5	—	Unverified
7	VehicleNet	mAP	83.41	—	Unverified
8	ProNet++ (ResNet50)	mAP	83.4	—	Unverified
9	TransReID	mAP	82.3	—	Unverified
10	CA-Jaccard	mAP	81.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Recall@k Surrogate loss (ViT-B/16)	Rank-1	96.2	—	Unverified
2	Recall@k Surrogate loss (ResNet-50)	Rank-1	95.7	—	Unverified
3	RPTM	Rank-1	95.5	—	Unverified
4	PNP Loss	Rank-1	95.5	—	Unverified
5	Smooth-AP	Rank-1	94.9	—	Unverified
6	MBR-4B (without RK)	Rank-1	88.3	—	Unverified
7	ANet	Rank-1	87.9	—	Unverified
8	CLIP-ReID (without re-ranking)	Rank-1	85.5	—	Unverified
9	GiT	Rank1	84.65	—	Unverified
10	HPGN	Rank1	83.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Recall@k Surrogate loss (ViT-B/16)	Rank-1	94.7	—	Unverified
2	Recall@k Surrogate loss (ResNet-50)	Rank-1	93.8	—	Unverified
3	PNP Loss	Rank-1	93.2	—	Unverified
4	RPTM	Rank-1	92.9	—	Unverified
5	Smooth-AP	Rank-1	91.9	—	Unverified
6	ANet	Rank-1	80.5	—	Unverified
7	vehiclenet	Rank-1	79.46	—	Unverified
8	MSINet (2.3M w/o RK)	Rank-1	77.9	—	Unverified
9	CAL	Rank-1	75.1	—	Unverified
10	QD-DLF	mAP	68.41	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Recall@k Surrogate loss (ViT-B/16)	Rank-1	95.2	—	Unverified
2	Recall@k Surrogate loss (ResNet-50)	Rank-1	94.6	—	Unverified
3	PNP Loss	Rank-1	94.2	—	Unverified
4	RPTM	Rank-1	93.3	—	Unverified
5	Smooth-AP	Rank-1	93.3	—	Unverified
6	ANet	Rank-1	82.8	—	Unverified
7	vehiclenet	Rank-1	81.35	—	Unverified
8	CAL	Rank-1	78.2	—	Unverified
9	QD-DLF	mAP	74.63	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Baseline Model	MAP	0.78	—	Unverified
2	abu_0916	MAP	0.78	—	Unverified
3	Juice Lee	MAP	0.7	—	Unverified
4	nanggg	MAP	0.63	—	Unverified
5	asdf	MAP	0.62	—	Unverified
6	92	MAP	0.56	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MBR-4B (without RK)	Rank1	96.6	—	Unverified
2	ANet	Rank1	96.5	—	Unverified
3	ResNet50-IBN	mAP	73.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Baseline Model	MAP	0.79	—	Unverified
2	Juice Lee	MAP	0.69	—	Unverified
3	nanggg	MAP	0.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	vehiclenet	mAP	83.41	—	Unverified
2	VKD (ResVKD-50)	mAP	82.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ANet	mAP	75.9	—	Unverified
2	ResNet50-IBN	mAP	58.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	A Strong Baseline	mAP	61.34	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VehicleNet	Rank1	83.64	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ANet	Rank1	95.2	—	Unverified