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个人简介
My name is Gabriel Brostow, and I am an associate professor (Reader) in Computer Science here at UCL. My group explores research problems relating to Computer Vision and Computer Graphics. The students and colleagues here have diverse interests, but my focus is on "Smart Capture" for analysis and synthesis applications. To me, smart capture of visual data (usually video) means having or finding satisfying answers to these questions about a system, whether interactive or fully automated:
I) Does the system know the intended purpose of the data being captured?
II) Can the system assess its own accuracy?
III) Does the system compare new inputs to old ones?
I love this field because it allows us to apply our expertise to a variety of tough problems, including film and photo special effects (computational photography), action analysis (of people, animals, and cells), and authoring systems (for architecture, animation, presentations) that make the most of user effort. "Motion reveals everything" used to be my main research mantra, but that has now taken hold sufficiently (obviously NOT just through my efforts!) that it no longer needs championing.
I) Does the system know the intended purpose of the data being captured?
II) Can the system assess its own accuracy?
III) Does the system compare new inputs to old ones?
I love this field because it allows us to apply our expertise to a variety of tough problems, including film and photo special effects (computational photography), action analysis (of people, animals, and cells), and authoring systems (for architecture, animation, presentations) that make the most of user effort. "Motion reveals everything" used to be my main research mantra, but that has now taken hold sufficiently (obviously NOT just through my efforts!) that it no longer needs championing.
研究兴趣
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Jamie Watson, Filippo Aleotti,Mohamed Sayed, Zawar Qureshi,Oisin Mac Aodha,Gabriel J. Brostow, Michael Firman,Sara Vicente
CVPR 2024 (2024)
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CVPR 2023 (2023): 16528-16538
CVPR 2023 (2023): 9053-9064
WACVpp.5839-5849, (2023)
CVPR 2023 (2023): 8979-8989
arXiv (Cornell University) (2022)
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