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pro vyhledávání: '"Zhang, Xuaner Cecilia"'
Autor:
Lin, Esther Y. H., Wang, Zhecheng, Lin, Rebecca, Miau, Daniel, Kainz, Florian, Chen, Jiawen, Zhang, Xuaner Cecilia, Lindell, David B., Kutulakos, Kiriakos N.
Optical blur is an inherent property of any lens system and is challenging to model in modern cameras because of their complex optical elements. To tackle this challenge, we introduce a high-dimensional neural representation of blur$-$$\textit{the le
Externí odkaz:
http://arxiv.org/abs/2310.11535
Autor:
Niklaus, Simon, Zhang, Xuaner Cecilia, Barron, Jonathan T., Wadhwa, Neal, Garg, Rahul, Liu, Feng, Xue, Tianfan
Traditional reflection removal algorithms either use a single image as input, which suffers from intrinsic ambiguities, or use multiple images from a moving camera, which is inconvenient for users. We instead propose a learning-based dereflection alg
Externí odkaz:
http://arxiv.org/abs/2010.00702
Autor:
Zhang, Xuaner Cecilia, Barron, Jonathan T., Tsai, Yun-Ta, Pandey, Rohit, Zhang, Xiuming, Ng, Ren, Jacobs, David E.
Casually-taken portrait photographs often suffer from unflattering lighting and shadowing because of suboptimal conditions in the environment. Aesthetic qualities such as the position and softness of shadows and the lighting ratio between the bright
Externí odkaz:
http://arxiv.org/abs/2005.08925
This paper shows that when applying machine learning to digital zoom for photography, it is beneficial to use real, RAW sensor data for training. Existing learning-based super-resolution methods do not use real sensor data, instead operating on RGB i
Externí odkaz:
http://arxiv.org/abs/1905.05169
Videos captured by consumer cameras often exhibit temporal variations in color and tone that are caused by camera auto-adjustments like white-balance and exposure. When such videos are sub-sampled to play fast-forward, as in the increasingly popular
Externí odkaz:
http://arxiv.org/abs/1709.10214
Akademický článek
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Akademický článek
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Autor:
Zhang, Xiuming, Srinivasan, Pratul P., Deng, Boyang, Debevec, Paul, Freeman, William T., Barron, Jonathan T.
Publikováno v:
ACM Transactions on Graphics; Dec2021, Vol. 40 Issue 6, p1-18, 18p
