정보통신대학
- 전자전기공학부
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조교수
기계학습/컴퓨터비전
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박은병
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학력
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- 2014~2019: University of North Carolina at Chapel Hill 컴퓨터공학 박사
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- 2009~2011: 서울대학교 컴퓨터공학 석사
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- 2002~2009: 경희대학교 컴퓨터공학 학사
약력/경력
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- 2021~ : 조교수, 성균관대학교
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- 2020~2021: Applied Scientist, Microsoft
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- 2019~2020: Research Scientist, Nuro
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- 2018: Research Intern, Google DeepMind
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- 2017: Research Intern, Microsoft Research
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- 2016: Research Intern, Adobe Research
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- 2015: Research Intern, HP Labs
학술회의논문
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(2023)
Mip-Grid: Anti-aliased Grid Representations for Neural Radiance Fields.
Conference on Neural Information Processing Systems.
미국
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(2023)
Separable Physics-Informed Neural Networks.
Conference on Neural Information Processing Systems.
미국
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(2023)
FFNeRV: Flow-Guided Frame-Wise Neural Representations for Videos.
ACM Multimedia Conference.
캐나다
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(2023)
Masked Wavelet Representation for Compact Neural Radiance Fields.
Conference on Computer Vision and Pattern Recognition.
캐나다
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(2023)
SMPConv: Self-moving Point Representations for Continuous Convolution.
Conference on Computer Vision and Pattern Recognition.
캐나다
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(2023)
PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers.
AAAI Conference on Artificial Intelligence.
미국
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(2022)
Neural Residual Flow Fields for Efficient Video Representations.
Asian Conference on Computer Vision.
중국
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(2022)
Streamable Neural Fields.
European Conference on Computer Vision.
이스라엘
