Liran Azaria

1paper

1 Paper

CVDec 15, 2020
Geometry Enhancements from Visual Content: Going Beyond Ground Truth

Liran Azaria, Dan Raviv

This work presents a new cyclic architecture that extracts high-frequency patterns from images and re-insert them as geometric features. This procedure allows us to enhance the resolution of low-cost depth sensors capturing fine details on the one hand and being loyal to the scanned ground truth on the other. We present state-of-the-art results for depth super-resolution tasks and as well as visually attractive, enhanced generated 3D models.