Learning View Priors for Single-view 3D Reconstruction

Understand

There is some ambiguity in the 3D shape of an object when the number of observed views is small.

• Because of this ambiguity, although a 3D object reconstructor can be trained using a single view or a few views per object, reconstructed shapes only fit the observed views and appear incorrect from the unobserved viewpoints.
• To reconstruct shapes that look reasonable from any viewpoint, we propose to train a discriminator that learns prior knowledge regarding possible views.
• The discriminator is trained to distinguish the reconstructed views of the observed viewpoints from those of the unobserved viewpoints.