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ResearchFormerly WizWand

Image Retrieval on Oxford 5k classic (base)

92.6mAPCiDeR-FT
36.23250.86665.580.134Apr 1, 2024
Updated 8mo ago

Evaluation results

MethodLinks
CiDeR-FTTrain Set=SfM-120k, Backbone=ResNet-101, Pooling=GeM, Loss=ArcFace, Fine-tuned=true, Dimension=20482024.0492.6
CiDeRTrain Set=SfM-120k, Backbone=ResNet-101, Pooling=GeM, Loss=ArcFace, Fine-tuned=false, Dimension=20482024.0489.9
GLAMTrain Set=SfM-120k, Backbone=ResNet-101, Pooling=GeM, Loss=ArcFace, Fine-tuned=true, Dimension=5122024.0489.7
Radenovic et al.Train Set=SfM-120k, Backbone=ResNet-101, Pooling=GeM, Loss=Siamese, Fine-tuned=true, Dimension=20482024.0487.8
DIR+RPNTrain Set=NC-clean, Backbone=ResNet-101, Pooling=RMAC, Loss=Triplet, Fine-tuned=true, End-to-End=true, Dimension=20482024.0485.2
Liao et al.Train Set=Oxford, Paris, Backbone=AlexNet, VGG16, Pooling=CroW, Loss=Softmax, Local, Fine-tuned=true, Dimension=7682024.0480.1
DIRTrain Set=SfM-120k, Backbone=ResNet-101, Pooling=RMAC, Loss=Triplet, Fine-tuned=true, Dimension=20482024.0479
SOLARTrain Set=SfM-120k, Backbone=ResNet-101, Pooling=GeM, Loss=Triplet, SOS, Fine-tuned=true, Dimension=20482024.0478.5
DOLGTrain Set=SfM-120k, Backbone=ResNet-101, Pooling=GeM,GAP, Loss=ArcFace, Fine-tuned=true, Dimension=5122024.0472.8
Salvador et al.Train Set=Pascal VOC, Backbone=VGG16, Pooling=Global Sum Pooling, Loss=Softmax, Local, Fine-tuned=true, Dimension=5122024.0467.9
Chen et al.Train Set=OpenImageV4, Backbone=ResNet-50, Pooling=MAC, Loss=Softmax, Local, Fine-tuned=true, Dimension=20482024.0450.2
Mei et al.Train Set=ImageNet (Off-the-shelf), Backbone=ResNet-101, Pooling=FC, Loss=Softmax, Fine-tuned=false, Dimension=40962024.0438.4