Planar Surface Reconstruction from Sparse Views
University of Michigan
ICCV 2021 (Oral)
Given two RGB images with an unknown relationship, our system
produces a coherent planar surface reconstruction of the scene in terms
of 3D planes and relative camera pose.
We show this reconstruction
with the inferred left and right cameras in Blue and Red
The paper studies planar surface reconstruction of indoor scenes from two views with unknown camera pose.
While prior approaches have successfully created object-centric reconstructions of many scenes,
they fail to exploit other structures, such as planes, which are typically the dominant components of indoor scenes.
In this paper, we reconstruct planar surfaces from multiple views, while jointly estimating camera pose.
Our experiments demonstrate that our method is able to advance the state of the art of reconstruction from sparse views,
on challenging scenes from Matterport3D.
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