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个人简介
Prof. Yi Fang directs the NYU Multimedia and Visual Computing Lab. He received his PhD from Purdue University with research focus on 3D computer vision. Upon one year industry experience as a research intern in Siemens in Princeton, New Jersey and a senior research scientist in Riverain Technologies in Dayton, Ohio, and a half-year academic experience as a senior staff scientist at Department of Electrical Engineering and Computer science, Vanderbilt University, Nashville, he has built well-round skill set and expertise in multimedia and visual computing and the applied fields in medicine and biology. He has developed a comprehensive and diverse research fields in large-scale 3D visual data processing. He is currently working on the development of state-of-the-art techniques in large-scale visual computing that consists of 3D scene understanding, data-driven 3D visual data processing, and deep cross-domain and cross-modality visual multimedia processing. The development in 3D scene understanding research enables a robust 3D dynamic scene reconstruction as well as explores the relations between visual/geometric features and semantic context information, the development in data-driven 3D visual data processing includes the techniques for 3D object registration, retrieval and segmentation that aim to discover geometric, structural, and semantic relationships between 3D objects in a large-scale collection, resulting in intelligent modeling, editing, and visualization of geometric data, and the development in cross-domain and cross-modality aims to robustly exploit the cross-representation for cross-domain and cross-modality objects retrieval as well as multi-view feature integration and fusion for the generation of decision level feature.
研究兴趣
论文共 159 篇作者统计合作学者相似作者
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Computers & Graphics (2024): 103891
Yan Luo,MIN SHI, Muhammad Osama Khan, Muhammad Muneeb Afzal,Hao Huang,Shuaihang Yuan,Yu Tian, Luo Song, Ava Kouhana,Tobias Elze,Yi Fang,Mengyu Wang
CVPR 2024 (2024)
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CoRR (2024)
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Machine Learning for Health Workshoppp.217-231, (2023)
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2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (2023): 11436-11442
2023 IEEE International Conference on Image Processing (ICIP)pp.2780-2784, (2023)
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CVPR 2023pp.21856-21865, (2023)
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