Vehicle Re-identification research benchmarks

Benchmarks

Dataset NameSOTA methodMetricTrendResultsLast Updated

V-Reid dataset

VehicleMAE-V2

87.3mAP

Feb 26, 2026

PKU-VehicleID → VeRi-776 unsupervised domain adaptation

Ours

76.9Rank-1 Accuracy

Feb 26, 2026

DetReIDX V1

DUT IIAU LAB

32.89mAP-3

Feb 26, 2026

VehicleID Medium

CLIP-ReID

81Rank-1

Feb 27, 2026

VeRi (test)

VGG-CNN-M-1024

1.872FET (ms/img)

Feb 26, 2026

VReID-XFD G→A

Scale-Aware Adaptation Framework

70.79Rank-1 Retrieval Rate (R1)

Apr 7, 2026

VReID-XFD A→G

Scale-Aware Adaptation Framework

41.42Rank-1 Accuracy

Apr 7, 2026

VReID-XFD A→A

DUT IIAU LAB

25.39Rank-1 (R1)

Apr 7, 2026

VehicleX-to-VeRi-776

AWB

37.2mAP (%)

Feb 26, 2026

VeRi-776

AQE

3.5Inference Time (ms)

Feb 26, 2026

AICity Challenge Private (test)

VehicleNet

86.07mAP (%)

Feb 26, 2026

VehicleID size 3200 (test)

PAL

42.13mAP

Feb 26, 2026

AliceVehicle

BMM

21.27FID

Feb 26, 2026

Our datatset

ViT Base + VC

81.82Top-1 Accuracy

May 7, 2026