2 papers with code • 0 benchmarks • 0 datasets
3D object super-resolution is the task of up-sampling 3D objects.
We consider the problem of scaling deep generative shape models to high-resolution.
Ranked #2 on 3D Object Reconstruction on Data3D−R2N2 (Avg F1 metric)
This paper proposes a 3D shape descriptor network, which is a deep convolutional energy-based model, for modeling volumetric shape patterns.