The Screen Annotation dataset consists of pairs of mobile screenshots and their annotations. The mobile screenshots are directly taken from the publicly available Rico dataset. The annotations are in text format, and contain information on the UI elements present on the screen: their type, their location, the text they contain or a short description. This dataset has been introduced in the paper ScreenAI: A Vision-Language Model for UI and Infographics Understanding and can be used to improve the screen understanding capabilities of multimodal (image+text) models.
All the screenshots are split following the splits proposed in Screen2Words: Automatic Mobile UI Summarization with Multimodal Learning.
Training, validation and test splits contain 15743 (~70%), 2364 (~10%) and 4310 (~20%) of all screenshots.
The data is stored in csv format. Each line contains the following 2 fields:
- image_id: Screenshot identifier in Rico dataset (should be used to get image bytes and other information tied to this screenshot).
- label: A description of the screenshot that identifies UI elements, their type, position, text, and description for images.
The labels were produced using automated techniques, and were verified and corrected by human raters.
If you use or discuss this dataset in your work, please cite our paper:
@misc{baechler2024screenai,
title={ScreenAI: A Vision-Language Model for UI and Infographics Understanding},
author={Gilles Baechler and Srinivas Sunkara and Maria Wang and Fedir Zubach and Hassan Mansoor and Vincent Etter and Victor Cărbune and Jason Lin and Jindong Chen and Abhanshu Sharma},
year={2024},
eprint={2402.04615},
archivePrefix={arXiv},
primaryClass={cs.CV}
}The dataset is licensed under CC BY 4.0.
If you have a technical question regarding the dataset or publication, please create an issue in this repository.