Instance Segmentation On Armbench
Metrics
AP50
AP75
Results
Performance results of various models on this benchmark
Model Name | AP50 | AP75 | Paper Title | Repository |
|---|---|---|---|---|
| RISE (R101) | 84.74 | 75.93 | Robot Instance Segmentation with Few Annotations for Grasping | - |
| Deformable DETR | 77.03 | 63.4 | Robot Instance Segmentation with Few Annotations for Grasping | - |
| RISE (R50) | 83.53 | 75.15 | Robot Instance Segmentation with Few Annotations for Grasping | - |
| Mask2Former | 81.2 | 74.0 | Robot Instance Segmentation with Few Annotations for Grasping | - |
| RISE (VIT-B) | 86.37 | 77.51 | Robot Instance Segmentation with Few Annotations for Grasping | - |
| RoboLLM (VIT-B) | 82.0 | 74 | RoboLLM: Robotic Vision Tasks Grounded on Multimodal Large Language Models | - |
| Mask R-CNN (Resnet50) | 72 | 61 | ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation | - |
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