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Description Research in our lab focuses on two intimately connected branches of vision research: computer vision and human vision. In both fields, we are intrigued by visual functionalities that give rise to semantically meaningful interpretations of the visual world. In computer vision, we aspire to develop intelligent algorithms that perform important visual perception tasks such as object recog
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We are working on various research topics in the field of computer vision with a particular focus on two areas: sensing and understanding of human activities, and modeling and understanding of object appearances. For Prospective StudentsOur group is affiliated with two graduate schools of the University of Tokyo: Department of Information and Communication Engineering, Graduate School of Informati
shirasy 2009/11/25
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At ACM UIST 2024, we will present the following research: Conductive Fabric Diaphragm for Noise-Suppressive Headset Microphone (Demos) Hirotaka Hiraki , Shusuke Kanazawa , Takahiro Miura , Manabu Yoshida , Masaaki Mochimaru , Jun Rekimoto Mapping Gaze and Head Movement via Salience Modulation and Hanger Reflex (Posters), Wanhui Li , Qing Zhang , Takuto Nakamura , Sinyu Lai , Jun Rekimoto Piezoelec
shirasy 2009/11/08
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The Tangible Media Group, led by Professor Hiroshi Ishii, pursues the vision of Tangible Bits & Radical Atoms to seamlessly couple the dual worlds of bits and atoms by giving dynamic physical form to digital information and computation. more on our vision A Graphical User Interface only lets us see information and interact with it indirectly, as if we were looking through the surface of the water
shirasy 2009/11/08
MIT Media Lab - Tangible Media Group

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Hyper Vision Research Laboratory Hyper Vision Research Laboratory (HVRL), Keio University, mainly focuses on Computer Vision research. Our research interests range from basic computer vision theories through applications including image recognition and understanding, broadcast image techno logy, and augmented reality. We have one paper accepted at MICCAI. Our paper: â€œDeep Selection: A Fully Supervi
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