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Scene Recognition on SUN 397 (val)

78.93AccuracySOSF+CFA+GAF
41.708451.371761.03570.6983Jul 17, 2019

Evaluation results

MethodLinks
SOSF+CFA+GAFAdditional data=Object177, Input Resolution=608x6082019.0778.93
FOSNetFusion Level=feature level, Fusion strategy=mixed CCM-CCG, Input Resolution=224x2242019.0777.28
FOSNetFusion Level=feature level, Fusion strategy=CCG, Input Resolution=224x2242019.0776.62
SE-ResNeXt-101 + SCLBackbone=SE-ResNeXt-101, Feature Mode=Single scene feature2019.0776.27
FOSNetFusion Level=feature level, Fusion strategy=Concatenate, Input Resolution=224x2242019.0775.57
FOSNetFusion Level=feature level, Fusion strategy=Sum, Input Resolution=224x2242019.0775.32
Adi-Red2019.0773.59
SDO2019.0773.41
PatchNet2019.0773
CNN-SMN2019.0772.6
Multi-Resolution CNNs2019.0772
Sparse Representation2019.0771.08
Hybrid CNN2019.0770.69
Three2019.0770.17
Places365-VGG-SVMBackbone=VGG, Pre-training=Places3652019.0763.24
MetaObject-CNN2019.0758.11
DAG-CNN2019.0756.2
Gaze Shifting-CNN+SVM2019.0756.2
VS-CNN2019.0743.14