Inverse Transport Networks

Chengqian Che
Chengqian Che
Fujun Luan
Fujun Luan

CoRR, Volume abs/1809.10820, 2018.

Cited by: 0|Bibtex|Views65
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Other Links: dblp.uni-trier.de|arxiv.org

Abstract:

We introduce inverse transport networks as a learning architecture for inverse rendering problems where, given input image measurements, we seek to infer physical scene parameters such as shape, material, and illumination. During training, these networks are evaluated not only in terms of how close they can predict groundtruth parameter...More

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