Neural networks have made exciting progress on unstructured 3D geometric data; which is changing the way we fundamentally approach problems in geometry processing. In this talk, I will discuss several works which facilitate 3D reconstruction from several different directions, including consolidating point clouds, estimating a globally consistent point normal orientation, and reconstructing a surface mesh. Finally, I will conclude with ongoing and future work in this direction, as well as other related areas.
The lecture will be recorded.
