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Geometry-aware Deep Network for Single-Image Novel View Synthesis
[article]
2018
arXiv
pre-print
This paper tackles the problem of novel view synthesis from a single image. In particular, we target real-world scenes with rich geometric structure, a challenging task due to the large appearance variations of such scenes and the lack of simple 3D models to represent them. Modern, learning-based approaches mostly focus on appearance to synthesize novel views and thus tend to generate predictions that are inconsistent with the underlying scene structure. By contrast, in this paper, we propose
arXiv:1804.06008v1
fatcat:wrz7dz75hffwvpbhlpqow2m474