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Instance Segmentation On Armbench
評価指標
AP50
AP75
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
| Paper Title | |||
|---|---|---|---|
| RISE (VIT-B) | 86.37 | 77.51 | Robot Instance Segmentation with Few Annotations for Grasping |
| RISE (R101) | 84.74 | 75.93 | Robot Instance Segmentation with Few Annotations for Grasping |
| RISE (R50) | 83.53 | 75.15 | Robot Instance Segmentation with Few Annotations for Grasping |
| RoboLLM (VIT-B) | 82.0 | 74 | RoboLLM: Robotic Vision Tasks Grounded on Multimodal Large Language Models |
| Mask2Former | 81.2 | 74.0 | Robot Instance Segmentation with Few Annotations for Grasping |
| Deformable DETR | 77.03 | 63.4 | Robot Instance Segmentation with Few Annotations for Grasping |
| Mask R-CNN (Resnet50) | 72 | 61 | ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation |
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