# ADE20K Dataset
This is the repository for the [ADE20K](http://groups.csail.mit.edu/vision/datasets/ADE20K/) dataset. We provide some [starter code](notebooks/ade20k_starter.ipynb) to analyze the dataset, basic statistics of the data and links to existing projects using ADE20K.

## Overview
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## Download dataset
To download the dataset, register in [this link](http://groups.csail.mit.edu/vision/datasets/ADE20K/request_data/). Once you are approved you will be able to download the data, following the [terms of use](http://groups.csail.mit.edu/vision/datasets/ADE20K/terms).

## ADE20K related projects
Here is a list of existing challenges and projects using ADE20K data. Contact us if you would like to include the dataset in a new benchmark.
* [MIT Scene Parsing Benchmark](https://github.com/CSAILVision/sceneparsing): A semantic segmentation benchmark, using a subset of 250 classes from ADE20K
* [Robust Vision Challenge](http://www.robustvision.net/): A challenge to evaluate the robustness of models to multiple datasets and tasks, including semantic and instance segmentation, depth prediction, optical flow, etc.

## Citation
If you use this data, please cite the following paper:

Zhou, B., Zhao, H., Puig, X., Xiao, T., Fidler, S., Barriuso, A., & Torralba, A. (2019). Semantic understanding of scenes through the ade20k dataset. International Journal of Computer Vision, 127(3), 302-321.

```
@article{zhou2019semantic,
  title={Semantic understanding of scenes through the ade20k dataset},
  author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Xiao, Tete and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
  journal={International Journal of Computer Vision},
  volume={127},
  number={3},
  pages={302--321},
  year={2019},
  publisher={Springer}
}
```