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ResearchFormerly WizWand

Active Grasping on PyBullet Simulation YCB objects (test)

316Success CountOurs
80.96141.98203264.02Nov 16, 2025
Updated 4mo ago

Evaluation results

MethodLinks
OursGrasping Method=Se3diff Calib, Active Learning Method=ActiveGrasp2025.11316192441790.02
Se3diff Calib + Random†Grasping Method=Se3diff Calib, Active Learning Method=Random†, Additional Views=8 more views than all other active methods2025.1130629293876.50.05
Se3diff Calib + RandomGrasping Method=Se3diff Calib, Active Learning Method=Random2025.1129725334574.250.06
Se3diff Calib + ActiveNGFGrasping Method=Se3diff Calib, Active Learning Method=ActiveNGF2025.11296283343740.06
Se3diff Calib + ACEGrasping Method=Se3diff Calib, Active Learning Method=ACE2025.11296273145740.07
Se3diff Calib + BreyerGrasping Method=Se3diff Calib, Active Learning Method=Breyer2025.1129526275273.750.05
Se3diff Scene + ActiveGraspGrasping Method=Se3diff Scene, Active Learning Method=ActiveGrasp2025.11294502333730.28
Se3diff Calib + FisherRFGrasping Method=Se3diff Calib, Active Learning Method=FisherRF2025.1129435264573.50.05
GSNet + ActiveNGFGrasping Method=GSNet, Active Learning Method=ActiveNGF2025.11249593662620.3
Se3diff + ActiveNGFGrasping Method=Se3diff, Active Learning Method=ActiveNGF2025.1123326726958.250.4
Contact Graspnet + ActiveNGFGrasping Method=Contact Graspnet, Active Learning Method=ActiveNGF2025.11130342820832.50.32
ACE + ACEGrasping Method=ACE, Active Learning Method=ACE2025.11901221682022.50.35