首页|New Robotics and Automation Study Results from Guangdong University of Technolog y Described (Distillgrasp: Integrating Features Correlation With Knowledge Disti llation for Depth Completion of Transparent Objects)
New Robotics and Automation Study Results from Guangdong University of Technolog y Described (Distillgrasp: Integrating Features Correlation With Knowledge Disti llation for Depth Completion of Transparent Objects)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Robotics - Ro botics and Automation have been published. According to news reporting originati ng from Guangzhou, People’s Republic of China, by NewsRx correspondents, researc h stated, “Due to the visual properties of reflection and refraction, RGB-D came ras cannot accurately capture the depth of transparent objects, leading to incom plete depth maps. To fill in the missing points, recent studies tend to explore new visual features and design complex networks to reconstruct the depth, howeve r, these approaches tremendously increase computation, and the correlation of di fferent visual features remains a problem.” Funders for this research include China Scholarship Council, National Natural Sc ience Foundation of China (NSFC), Special Research Fund (BOF) of Hasselt Univers ity, The foundation of State Key Laboratory of Public Big Data, Guangdong Innova tive Research Team Program.
GuangzhouPeople’s Republic of ChinaA siaRobotics and AutomationRoboticsGuangdong University of Technology
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