Object Detection on SUNRGB-D v1 (test)
36.6mAP (All)Faster R-CNN (Teacher)
Evaluation results
| Method | Links | |||||||
|---|---|---|---|---|---|---|---|---|
| Faster R-CNN (Teacher)Backbone=Res50 (×2), Input=RGB-D2024.05 | 36.6 | 57.8 | 30.7 | 42.4 | 38.9 | 61.3 | 13.8 | |
| Faster R-CNN (Student) w/ AMFDBackbone=Res18 (×1), Input=RGB-D2024.05 | 36.5 | 56 | 31.7 | 41.5 | 39.2 | 61.3 | 14.5 | |
| Faster R-CNN (Student)Backbone=Res18 (×1), Input=RGB-D2024.05 | 32.1 | 50.9 | 28.3 | 36.5 | 34.9 | 53.3 | 11.1 | |
| Faster R-CNNBackbone=Res50 (×2), Input=RGB2024.05 | 30.6 | 44.2 | 28.5 | 32.1 | 36.6 | 51.9 | 10.7 | |
| Faster R-CNNBackbone=Res18 (×1), Input=Depth2024.05 | 30.5 | 46.3 | 25.7 | 34.2 | 33.3 | 53.3 | 11.4 | |
| Faster R-CNNBackbone=Res18 (×1), Input=RGB2024.05 | 30.2 | 43.9 | 24.5 | 33.9 | 33.2 | 53.6 | 10.3 | |
| Faster R-CNNBackbone=Res50 (×2), Input=Depth2024.05 | 29.5 | 52.9 | 27.4 | 34.1 | 34.3 | 54.4 | 8 |