ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes

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.

Calendar October 22, 2023