Scene Recognition on MIT indoor 67 (val)
68.43Top-1 AccuracyFiGKD
Evaluation results
| Method | Links | ||
|---|---|---|---|
| FiGKDTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 68.43 | — | |
| FiGKDTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 65.67 | — | |
| MLKDTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 65.35 | — | |
| PKTTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 64.73 | — | |
| DKDTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 64.35 | — | |
| CRDTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 63.92 | — | |
| RKDTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 62.14 | — | |
| MLKDTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 61.89 | — | |
| KDTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 61.87 | — | |
| TeacherTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 61.64 | — | |
| ATTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 61.22 | — | |
| PKTTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 60.8 | — | |
| ReviewKDTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 60.76 | — | |
| ATTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 60.6 | — | |
| DKDTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 60 | — | |
| CRDTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 59.7 | — | |
| ReviewKDTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 59.68 | — | |
| TeacherTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 59.55 | — | |
| KDTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 58.78 | — | |
| FitNetTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 58.28 | — | |
| RKDTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 57.63 | — | |
| StudentTeacher Architecture=ResNet34, Student Architecture=ResNet182025.05 | 57.49 | — | |
| StudentTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 57.49 | — | |
| FitNetTeacher Architecture=MobileNetV1, Student Architecture=ResNet182025.05 | 57.07 | — | |
| Adi-Red2019.07 | — | 73.59 | |
| CNN-SMN2019.07 | — | 86.5 | |
| DAG-CNN2019.07 | — | 77.5 | |
| DPM+GIST+SPfeatures=handcrafted2019.07 | — | 43.1 | |
| FOSNetfusion=Sum, input_size=224x2242019.07 | — | 88.73 | |
| FOSNetfusion=Concatenate, input_size=224x2242019.07 | — | 89.25 | |
| FOSNetfusion=CCG, input_size=224x2242019.07 | — | 90.37 | |
| FOSNetfusion=mixed CCM-CCG, input_size=224x2242019.07 | — | 90.3 | |
| Gaze Shifting-CNN+SVM2019.07 | — | 75.1 | |
| Hybrid CNN2019.07 | — | 85.97 | |
| MetaObject-CNN2019.07 | — | 78.9 | |
| Multi-Resolution CNNs2019.07 | — | 86.7 | |
| PatchNet2019.07 | — | 86.2 | |
| Places365-VGG-SVMbackbone=VGG, pre-training=Places3652019.07 | — | 76.53 | |
| RBOWfeatures=handcrafted2019.07 | — | 37.93 | |
| ResNet-152-DFT+backbone=ResNet-1522019.07 | — | 76.5 | |
| SDO2019.07 | — | 86.76 | |
| SE-ResNeXt-101 + SCLbackbone=SE-ResNeXt-1012019.07 | — | 89.1 | |
| SOSF+CFA+GAFinput_size=608x6082019.07 | — | 89.51 | |
| Sparse Representation2019.07 | — | 87.22 | |
| Three2019.07 | — | 86.04 | |
| VS-CNN2019.07 | — | 80.37 |