https://github.com/ericsujw/Matterport3DLayoutAnnotation
Layout annotation on a subset of Matterport3D dataset
https://github.com/ericsujw/Matterport3DLayoutAnnotation
3d-layout 3d-reconstruction computer-vision room-layout
Last synced: 7 months ago
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Layout annotation on a subset of Matterport3D dataset
- Host: GitHub
- URL: https://github.com/ericsujw/Matterport3DLayoutAnnotation
- Owner: ericsujw
- Created: 2019-10-20T21:35:08.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2020-12-28T12:47:47.000Z (over 5 years ago)
- Last Synced: 2024-04-30T20:33:44.438Z (about 2 years ago)
- Topics: 3d-layout, 3d-reconstruction, computer-vision, room-layout
- Size: 1.52 MB
- Stars: 61
- Watchers: 6
- Forks: 9
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-holistic-3d - MatterportLayout - | n/a | 2,295 (RGB-D pano) | Manhattan layout | (Datasets / Scene level)
README
# The MatterportLayout dataset
This dataset extends the Matterport3D dataset with general Manhattan layout annotations and is used in our work "[Manhattan Room Layout Reconstruction from a Single 360° image: A Comparative Study of State-of-the-art Methods](http://arxiv.org/abs/1910.04099)" for performance evaluation.
## Pre-processing
We released only the annotated layout files. To generate the corresponding RGB panoramas, use the following instructions:
1. Download the **[Matterport3D](https://github.com/niessner/Matterport)** dataset.
2. Follow the Matlab codes in **[PanoBasic/demo_matterport.m](https://github.com/yindaz/PanoBasic/blob/master/demo_matterport.m#L44)** to stitch the skybox images of the Matterport3D into the equirectangular panoramas.
3. Run the script provided in **[PanoAnnotator/pre-process](https://github.com/SunDaDenny/PanoAnnotator#pre-process)** to generate Manhattan-aligned panoramas.
## Data format
* **Panorama list**: The dataset includes 2295 panoramas selected from the Matterport3D dataset and we split the images into [train](data_list/mp3d_train.txt)/[val](data_list/mp3d_val.txt)/[test](data_list/mp3d_test.txt) lists.
* **Annotation format**: We use the same the annotation format as [DuLa-Net](https://github.com/SunDaDenny/DuLa-Net) and [PanoAnnotator](https://github.com/SunDaDenny/PanoAnnotator). An example json file is shown below. Please refer to these two repos for more details. Note that we've aligned all the annotated layouts to the camera height of 1.6m.
```javascript
{
"cameraHeight": 1.6, // distance between camera and floor
"layoutHeight": 2.9809624004364013, // distance between floor and ceiling
"layoutObj2ds": { // door or window labeling block
"num": 0,
"obj2ds": []
},
"layoutPoints": { // corner labeling block, we only annotate the corner in the horizontal direction because you can easily get the corner in the vertical direction from cameraHeight and layoutHeight.
"num": 6, // corner number in the horizontal direction
"points": [ // List of the corner
{
"coords": [ // uv coordintate of the corner on the panorama
0.7081447345651483, // u coordintate of the corner on the panorama
0.5 // v coordintate of the corner on the panorama. We annotate on horizon line, then calculate the vertical position by cameraHeight and layoutHeight.
],
"id": 0, // id number
"xyz": [ // project the corner on to the 3D coordinate
3.0078125, // x value
0.0, // y value
-0.8097623087756155 // z value
]
},
{...}
]
},
"layoutWalls": { // layout walls represented by plane equation
"num": 6, // wall number
"walls": [ // list of wall
{
"id": 0, // id number
"normal": [ // plane equation's normal
1.0,
0.0,
-0.0
],
"planeEquation": [ // plane equation
1.0, // a
0.0, // b
-0.0, // c
-3.0078125 // d
],
"pointsIdx": [ // which two points construct this wall
0,
1
],
"width": 2.8476272687756152 // the wall width
},
{...}
]
},
"panoId": "nothing" // a simple ID of panorama
}
```
* **File name**: We zip all the annotation files in the [label_data.zip](label_data.zip). The filename `__label.json` follows the folder structure of Matterport3D dataset.
## Citation
If you use this dataset for your research, please cite our paper as follows:
```
@article{zou20193d,
title={Manhattan Room Layout Reconstruction from a Single 360$^{\circ}$ image: A Comparative Study of State-of-the-art Methods},
author={Zou, Chuhang and Su, Jheng-Wei and Peng, Chi-Han and Colburn, Alex and Shan, Qi and Wonka, Peter and Chu, Hung-Kuo and Hoiem, Derek},
journal={arXiv preprint arXiv:1910.04099},
year={2019}
}
```
## License
The data is released under the [Matterport3D Terms of Use](http://kaldir.vc.in.tum.de/matterport/MP_TOS.pdf), and the code is released under the MIT license. By using this dataset, you agree to all the terms in the [Matterport3D Terms of Use](http://kaldir.vc.in.tum.de/matterport/MP_TOS.pdf).
## Acknowledgement
For all the layouts in the dataset, we started with initial layouts from [LayoutMP3D](https://arxiv.org/abs/2011.11498), which is also annotated with **[PanoAnnotator](https://github.com/SunDaDenny/PanoAnnotator)**.