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Found 5 papers, 2 papers with code
Neural Semantic Surface Maps
We present an automated technique for computing a map between two genus-zero shapes, which matches semantically corresponding regions to one another.
Neural Convolutional Surfaces
Our pipeline and architecture are designed so that disentanglement of global geometry from local details is accomplished through optimization, in a completely unsupervised manner.
Neural Surface Maps
Maps are arguably one of the most fundamental concepts used to define and operate on manifold surfaces in differentiable geometry.
Dense 3D Visual Mapping via Semantic Simplification
Dense 3D visual mapping estimates as many as possible pixel depths, for each image.
Predicting the Next Best View for 3D Mesh Refinement
Finding the best poses to capture part of the scene is one of the most challenging topic that goes under the name of Next Best View.
