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Vehicle Re-identification on VehicleID

86.6Rank-1 AccuracyPartFormer*
69.9674.2878.682.92Mar 13, 2023Sep 20, 2023Mar 30, 2024Oct 8, 2024Apr 17, 2025Oct 26, 2025May 6, 2026

Evaluation results

MethodLinks
PartFormer*Backbone=ViT-Base, Sliding window setting=true2024.0886.698—
MsKAT†Backbone=ViT-Base, Hybrid architecture (CNN and ViT)=true2024.0886.397.4—
BIDABackbone=ResNet-502024.0886.297.3—
TransReID*Backbone=ViT-Base, Sliding window setting=true2024.0885.297.5—
PartFormerBackbone=ViT-Base2024.0884.997.4—
DFNetBackbone=ResNet-502024.0884.896.2—
PVENBackbone=ResNet-502024.0884.797—
GiT*Backbone=ViT-Base, Sliding window setting=true2024.0884.7——
HPGNBackbone=ResNet-502024.0883.9——
TransReIDBackbone=ViT-Base2024.0883.697.1—
MMNetBackbone=ResNet-502024.0882.195.3—
CFVMNetBackbone=ResNet-502024.0881.494.1—
UMTSBackbone=ResNet-502024.0880.987—
ViT Base + VCDomain=RGB, Num Cls=2502026.0578.486.857.62
SPANDomain=RGB, Num Cls=2502026.0578.2285.1656.1
MSINet-SAMParams=2.4M, Inference Time=0.71×, Pre-training=ImageNet2023.037891.9—
PGANBackbone=ResNet-502024.087893.2—
MSINetParams=2.3M, Inference Time=0.71×, Pre-training=ImageNet2023.0377.991.7—
SN++Backbone=ResNet-502024.0876.787—
MSINetParams=2.3M, Inference Time=0.71×, Pre-training=Scratch2023.0376.589.8—
ResNet50Params=~24M, Inference Time=1×, Pre-training=ImageNet2023.0376.589.9—
OSNetParams=2.2M, Inference Time=0.79×, Pre-training=Scratch2023.037688.7—
OSNetParams=2.2M, Inference Time=0.79×, Pre-training=ImageNet2023.037688.6—
CDNetParams=1.8M, Inference Time=0.67×, Pre-training=Scratch2023.0374.588.8—
ViT BaseDomain=RGB, Num Cls=2502026.0571.48252.02
ResNet50Params=~ 24M, Inference Time=1×, Pre-training=Scratch2023.0370.676.6—