ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes
@inproceedings{dai2017scannet,
title={ScanNet: Richly-annotated 3d reconstructions of indoor scenes},
author={Dai, Angela and Chang, Angel X and Savva, Manolis and Halber, Maciej and Funkhouser, Thomas and Nie{\ss}ner, Matthias},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={5828--5839},
year={2017}
}
RGB-D video dataset containing 2.5M views in 1513 scenes annotated with 3D camera poses, surface reconstructions, and semantic segmentations.
- Semantic Scene Segmentation
- Get an “upvector” somehow
- Step throug the scene colum by colum and use neighbors for kernel