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Multi-view Supervision for Single-view Reconstruction via Differentiable Ray Consistency
[article]
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
arXiv:1704.06254v1
fatcat:xmzflirmizdx7a5iq62yq75k2m