首页|Investigators from Technical University Munich (TU Munich) Release New Data on R obotics and Automation (Improving Selfsupervised Learning of Transparent Catego ry Poses With Language Guidance and Implicit Physical Constraints)
Investigators from Technical University Munich (TU Munich) Release New Data on R obotics and Automation (Improving Selfsupervised Learning of Transparent Catego ry Poses With Language Guidance and Implicit Physical Constraints)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News ; Current study results on Robotics - Ro botics and Automation have been published.According to news reporting out of Mu nich, Germany, by NewsRx editors, research stated, “Accurate objectpose estimat ion is crucial for robotic applications and recent trends in category-level pose estimation showgreat potential for applications encountering a large variety o f similar objects, often encountered in homeenvironments. While common in such environments, photometrically challenging objects with transparencysuch as glas ses are poorly handled by current methods.”
MunichGermanyEuropeRobotics and Au tomationRoboticsEmerging TechnologiesMachine LearningSupervised LearningTechnical University Munich (TU Munich)
NETL
NSTL
