PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds

Understand

We introduce PC2WF, the first end-to-end trainable deep network architecture to convert a 3D point cloud into a wireframe model.

• The network takes as input an unordered set of 3D points sampled from the surface of some object, and outputs a wireframe of that object, i.e., a sparse set of corner points linked by line segments.
• Recovering the wireframe is a challenging task, where the numbers of both vertices and edges are different for every instance, and a-priori unknown.
• Our architecture gradually builds up the model: It starts by encoding the points into feature vectors.