The basic idea is to represent any object as a non-rigidly deformed canonical three-dimensional volume. Our method jointly learns the canonical volume and its deformations during training. We can also use the deformations to compute dense correspondences between visualized images.
Testimonials about Learning a 3D Generative Model with Disentangled Geometry and Appearance from Monocular Images
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