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Visual perception entails solving a wide set of tasks, e.g., object detection, depth estimation, etc.
Back-translation for cross-cultural research
Richard W. Brislin · 1970
Earlier work this paper cites.
Differential Topology
V. Guillemin and A. Pollack · 1974
Earlier work this paper cites.
Image analogies
Aaron Hertzmann, Charles E Jacobs, Nuria Oliver, Brian Curless, and David H Salesin · 2001
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
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Ravi Garg, Vijay Kumar BG, Gustavo Carneiro, and Ian Reid · 2016
Earlier work this paper cites.
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Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros · 2016
Earlier work this paper cites.
Perceptual losses for real-time style transfer and super-resolution
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Earlier work this paper cites.
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Later among the works it cites.
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Later among the works it cites.
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Later among the works it cites.
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Yuxin Wu and Kaiming He · 2018
Later among the works it cites.
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Later among the works it cites.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
Simple and scalable predictive uncertainty estimation using deep ensembles
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Cited alongside, same era.
Tolerances and uncertainty in robotic systems
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Cited alongside, same era.
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Cited alongside, same era.
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Later among the works it cites.
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The replica dataset: A digital replica of indoor spaces
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Enforcing geometric constraints of virtual normal for depth prediction
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Which Tasks Should Be Learned Together in Multi-task Learning?
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