報告題目：Understanding point clouds through geometric decriptors and natural language
報告人：Fabio Poiesi 博士
工作單位：意大利FBK研究院
時間：2024年12月26日（星期四）16:00
地點：太陽集團tyc5997翡翠科教樓A座1104
報告簡介：
Three-dimensional artificial perception enables robots to comprehend their environments and interact with objects to accomplish human-directed tasks. This talk explores novel approaches to point cloud understanding through the integration of geometric descriptors and natural language processing. We examine applications in robotic navigation and manipulation, with particular emphasis on four key downstream tasks: point cloud registration, 6D object pose estimation, functional segmentation, and dense captioning.
報告人簡介：
Fabio Poiesi is the Head of the Technologies of Vision Lab at Fondazione Bruno Kessler in Trento, Italy. He completed his PhD and Postdoctoral research at Queen Mary University of London. He joined FBK in 2016 as a Research Scientist and became a tenured researcher in 2023. His work focuses on developing computer vision and deep learning solutions for both research and real-world industrial applications. Fabio Poiesi has been working on algorithms for multi-object tracking and target behavior understanding since 2010. At FBK, he works on 3D scene understanding techniques for point cloud registration and understanding, using geometric techniques and natural language processing, which he has particularly applied to robotic perception for object manipulation. He has developed world-leading solutions for object 6D pose estimation, winning the popular BOP Challenge multiple times against competitors like NaverLabs, NVIDIA, and META. He is a member of the ELLIS network.
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