Command Palette
Search for a command to run...
Robot Manipulation Generalization On Gembench
평가 지표
Average Success Rate
Average Success Rate (L1)
Average Success Rate (L2)
Average Success Rate (L3)
Average Success Rate (L4)
평가 결과
이 벤치마크에서 각 모델의 성능 결과
| Paper Title | ||||||
|---|---|---|---|---|---|---|
| 3D-LOTUS++ | 48.0 | 68.7±0.6 | 64.5±0.9 | 41.5±1.8 | 17.4±0.4 | Towards Generalizable Vision-Language Robotic Manipulation: A Benchmark and LLM-guided 3D Policy |
| 3D-LOTUS | 45.7 | 94.3±1.4 | 49.9±2.2 | 38.1±1.1 | 0.3±0.3 | Towards Generalizable Vision-Language Robotic Manipulation: A Benchmark and LLM-guided 3D Policy |
| 3D diffuser actor | 44.0 | 91.9±0.8 | 43.4±2.8 | 37.0±2.2 | 0.0±0.0 | 3D Diffuser Actor: Policy Diffusion with 3D Scene Representations |
| RVT-2 | 44.0 | 89.1±0.8 | 51.0±2.3 | 36.0±2.2 | 0.0±0.0 | RVT-2: Learning Precise Manipulation from Few Demonstrations |
| PolarNet | 38.4 | 77.7±0.9 | 37.1±1.4 | 38.5±1.7 | 0.1±0.2 | PolarNet: 3D Point Clouds for Language-Guided Robotic Manipulation |
| Hiveformer | 30.4 | 60.3±1.5 | 26.1±1.4 | 35.1±1.7 | 0.0±0.0 | Instruction-driven history-aware policies for robotic manipulations |
0 of 6 row(s) selected.