| --- |
| language: |
| - en |
| license: bsd |
| size_categories: |
| - 1K<n<10K |
| pretty_name: arkit_labelmaker |
| viewer: false |
| tags: |
| - 3D semantic segmentation |
| - indoor 3D scene dataset |
| - pointcloud-segmentation |
| task_categories: |
| - image-segmentation |
| --- |
| |
| # ARKit Labelmaker: A New Scale for Indoor 3D Scene Understanding |
|
|
| [[arxiv]](https://arxiv.org/abs/2410.13924) [[website]](https://labelmaker.org/) [[checkpoints]](https://huggingface.co/labelmaker/PTv3-ARKit-LabelMaker) [[code]](https://github.com/cvg/LabelMaker) |
|
|
| We complement ARKitScenes dataset with dense semantic annotations that are automatically generated at scale. This produces the first large-scale, real-world 3D dataset with dense semantic annotations. |
| Training on this auto-generated data, we push forward the state-of-the-art performance on ScanNet and ScanNet200 with prevalent 3D semantic segmentation models. |
