English

Geometry Enhancements from Visual Content: Going Beyond Ground Truth

Computer Vision and Pattern Recognition 2022-03-08 v3

Abstract

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.

Keywords

Cite

@article{arxiv.2012.08248,
  title  = {Geometry Enhancements from Visual Content: Going Beyond Ground Truth},
  author = {Liran Azaria and Dan Raviv},
  journal= {arXiv preprint arXiv:2012.08248},
  year   = {2022}
}
R2 v1 2026-06-23T20:59:02.974Z