Robotic Grasping On Graspnet 1Billion
Métriques
AP_novel
AP_seen
AP_similar
mAP
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | AP_novel | AP_seen | AP_similar | mAP | Paper Title | Repository |
|---|---|---|---|---|---|---|
| graspness-CD | 24.31 | 67.12 | 54.81 | 48.75 | Graspness Discovery in Clutters for Fast and Accurate Grasp Detection | |
| Scale-Balanced-Grasp-CD | 24.63 | 63.83 | 58.46 | 48.97 | Towards Scale Balanced 6-DoF Grasp Detection in Cluttered Scenes | |
| HGGD-CD | 24.59 | 64.45 | 53.59 | 47.54 | Efficient Heatmap-Guided 6-Dof Grasp Detection in Cluttered Scenes | |
| graspnet-baseline-CD | 16.61 | 47.47 | 42.27 | 35.45 | GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping | |
| FlexLoG-CD | 30.04 | 72.81 | 65.21 | 56.02 | Rethinking 6-Dof Grasp Detection: A Flexible Framework for High-Quality Grasping | - |
| graspnet-baseline | 10.55 | 27.56 | 26.11 | 21.41 | GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping | |
| HGGD | 22.17 | 59.36 | 51.20 | 44.24 | Efficient Heatmap-Guided 6-Dof Grasp Detection in Cluttered Scenes |
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