Object Recognition on Washington RGB-D Object Dataset
92.3Avg Acc (RGB)ResNet101-RNN
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| ResNet101-RNNBackbone=ResNet1012020.04 | 92.3 | 87.2 | 94.1 | |
| DenseNet121-RNNBackbone=DenseNet1212020.04 | 91.5 | 86.9 | 93.5 | |
| VGG_f-RNN2020.04 | 89.9 | 84 | 92.5 | |
| MDSI-CNN2020.04 | 89.9 | 84.9 | 92.8 | |
| AlexNet-RNNAuthor=Bui et al.2020.04 | 89.7 | — | — | |
| RCFusion2020.04 | 89.6 | 85.9 | 94.4 | |
| DECO2020.04 | 89.5 | 84 | 93.6 | |
| Fusion 2D/3D CNNs2020.04 | 89 | 78.4 | 91.8 | |
| STEM-CaRFs2020.04 | 88.8 | 80.8 | 92.2 | |
| HP-CNN2020.04 | 87.6 | 85 | 91.1 | |
| CFK2020.04 | 86.8 | 85.8 | 91.2 | |
| CNN-SPM-RNN2020.04 | 85.2 | 83.6 | 90.7 | |
| MM-LRF-ELM2020.04 | 84.3 | 82.9 | 89.6 | |
| Fus-CNN2020.04 | 84.1 | 83.8 | 91.3 | |
| MMFLAN2020.04 | 83.9 | 84 | 93.1 | |
| CNN Features2020.04 | 83.1 | — | 89.4 | |
| AlexNet-RNNBackbone=AlexNet2020.04 | 83 | 84.1 | 90.9 | |
| Subset-RNN2020.04 | 82.8 | 81.8 | 88.5 | |
| CNN-RNN2020.04 | 80.8 | 78.9 | 86.8 | |
| KDES2020.04 | 77.7 | 78.8 | 86.2 | |
| MMDL2020.04 | 74.6 | 75.5 | 86.9 | |
| Kernel SVM2020.04 | 74.5 | 64.7 | 83.9 | |
| CaRFs2020.04 | — | — | 88.1 |