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arXiv · 1712.01812

Factoring Shape, Pose, and Layout from the 2D Image of a 3D Scene

Shubham Tulsiani·Saurabh Gupta·David Fouhey·Alexei A. Efros·Jitendra Malik
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Abstract

The goal of this paper is to take a single 2D image of a scene and recover the 3D structure in terms of a small set of factors: a layout representing the enclosing surfaces as well as a set of objects represented in terms of shape and pose. We propose a convolutional neural network-based approach to predict this representation and benchmark it on a large dataset of indoor scenes. Our experiments evaluate a number of practical design questions, demonstrate that we can infer this representation, and quantitatively and qualitatively demonstrate its merits compared to alternate representations.

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Shubham Tulsiani, Saurabh Gupta, David Fouhey, Alexei A. Efros, Jitendra Malik. 2017-12-05. Factoring Shape, Pose, and Layout from the 2D Image of a 3D Scene. https://arxiv.org/abs/1712.01812

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