Multi-view Supervision for Single-view Reconstruction via Differentiable Ray Consistency [article]

Shubham Tulsiani, Tinghui Zhou, Alexei A. Efros, Jitendra Malik
2017 arXiv   pre-print
We study the notion of consistency between a 3D shape and a 2D observation and propose a differentiable formulation which allows computing gradients of the 3D shape given an observation from an arbitrary view. We do so by reformulating view consistency using a differentiable ray consistency (DRC) term. We show that this formulation can be incorporated in a learning framework to leverage different types of multi-view observations e.g. foreground masks, depth, color images, semantics etc. as
more » ... vision for learning single-view 3D prediction. We present empirical analysis of our technique in a controlled setting. We also show that this approach allows us to improve over existing techniques for single-view reconstruction of objects from the PASCAL VOC dataset.
arXiv:1704.06254v1 fatcat:xmzflirmizdx7a5iq62yq75k2m