Grasp Detection on Cornell Dataset (image-wise)
97.7AccuracyFCGN, ResNet-101
Evaluation results
| Method | Links | ||
|---|---|---|---|
| FCGN, ResNet-101Authors=Zhou, Speed (ms)=1172019.09 | 97.7 | — | |
| GR-ConvNet-RGB-DAuthors=Our, Input=RGB-D, Speed (ms)=202019.09 | 97.7 | — | |
| GR-ConvNet-RGBAuthors=Our, Input=RGB, Speed (ms)=192019.09 | 96.6 | — | |
| Ours: Res-50 (RGB-D)Backbone=ResNet-50, Input Modality=RGB-D2018.02 | 96 | 8.33 | |
| Ours: VGG-16Backbone=VGG-16, Input Modality=RGB-D2018.02 | 95.5 | 17.24 | |
| Ours: Res-50 (RGB)Backbone=ResNet-50, Input Modality=RGB2018.02 | 94.4 | 8.33 | |
| Guo et al.2018.02 | 93.2 | — | |
| ZF-netAuthors=Guo2019.09 | 93.2 | — | |
| GR-ConvNet-DAuthors=Our, Input=Depth, Speed (ms)=192019.09 | 93.2 | — | |
| Mahler et al.2018.02 | 93 | 1.25 | |
| GraspNetAuthors=Asif, Speed (ms)=242019.09 | 90.2 | — | |
| Kumra et al.2018.02 | 89.2 | 16.03 | |
| ResNet-50x2Authors=Kumra, Speed (ms)=1032019.09 | 89.2 | — | |
| GRPNAuthors=Karaoguz, Speed (ms)=2002019.09 | 88.7 | — | |
| Asif et al.2018.02 | 88.2 | — | |
| STEM-CaRFsAuthors=Asif2019.09 | 88.2 | — | |
| Redmon et al.2018.02 | 88 | 3.31 | |
| AlexNet, MultiGraspAuthors=Redmon, Speed (ms)=762019.09 | 88 | — | |
| Two-stage closed-loopAuthors=Wang, Speed (ms)=1402019.09 | 85.3 | — | |
| Wang et al.2018.02 | 81.8 | 7.1 | |
| Lenz et al.2018.02 | 73.9 | 0.07 | |
| SAE, struct. reg.Authors=Lenz, Speed (ms)=13502019.09 | 73.9 | — | |
| GG-CNNAuthors=Morrison, Speed (ms)=192019.09 | 73 | — | |
| Jiang et al.2018.02 | 60.5 | 0.02 | |
| Fast SearchAuthors=Jiang, Speed (ms)=50002019.09 | 60.5 | — |