Statements (18)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:academic_journal
|
| gptkbp:author |
Andreas Geiger
Ali Osman Ulusoy Gernot Riegler |
| gptkbp:citation |
over 500 (as of 2024)
|
| gptkbp:contribution |
enables high-resolution 3D shape generation with efficient memory usage
proposes a deep learning framework for generating 3D shapes using octree representations |
| gptkbp:field |
computer vision
3D reconstruction 3D deep learning |
| https://www.w3.org/2000/01/rdf-schema#label |
Octree Generating Networks
|
| gptkbp:method |
octree-based convolutional neural networks
|
| gptkbp:publicationYear |
2017
|
| gptkbp:publishedIn |
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
|
| gptkbp:repository |
https://github.com/octree-nn/OctreeGeneration
|
| gptkbp:url |
https://arxiv.org/abs/1703.09438
|
| gptkbp:bfsParent |
gptkb:Maxim_Tatarchenko
|
| gptkbp:bfsLayer |
7
|