Update README.md

README.md

@@ -21,5 +21,230 @@ tags:
 - Diversity
 pretty_name: ArtELingo
 size_categories:
+- 10K<n<100K
+- 100K<n<1M
 - 1M<n<10M
----
+multilinguality:
+- multilingual
+source_datasets:
+- original
+---
+# Dataset Card for "ArtELingo"
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Dataset Configurations](#dataset-configurations)
+  - [Data Fields](#data-fields)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [artelingo.org/](https://www.artelingo.org/)
+- **Repository:** [More Information Needed](https://github.com/Vision-CAIR/artelingo)
+- **Paper:** [More Information Needed](https://arxiv.org/abs/2211.10780)
+- **Point of Contact:** [More Information Needed]([email protected])
+
+### Dataset Summary
+
+ArtELingo is a benchmark and dataset introduced in a research paper aimed at promoting work on diversity across languages and cultures. 
+It is an extension of ArtEmis, which is a collection of 80,000 artworks from WikiArt with 450,000 emotion labels and English-only captions. 
+ArtELingo expands this dataset by adding 790,000 annotations in Arabic and Chinese. 
+The purpose of these additional annotations is to evaluate the performance of "cultural-transfer" in AI systems.
+
+The goal of ArtELingo is to encourage research on multilinguality and culturally-aware AI. 
+By including annotations in multiple languages and considering cultural differences, 
+the dataset aims to build more human-compatible AI that is sensitive to emotional nuances 
+across various cultural contexts. The researchers believe that studying emotions in this 
+way is crucial to understanding a significant aspect of human intelligence.
+
+### Supported Tasks and Leaderboards
+
+We have two tasks:
+ - [Emotion Label Prediction](https://eval.ai/web/challenges/challenge-page/2106/overview)
+ - [Affective Image Captioning](https://eval.ai/web/challenges/challenge-page/2104/overview)
+
+Both challenges have a leaderboard on Eval.ai. Submission deadlines can be viewed from the above links.
+
+In addition, we are hosting the challenge at the ICCV23 workshop [WECIA](https://iccv23-wecia.github.io/). We have cash prizes for winners.
+
+### Languages
+
+We have 3 languages: English, Arabic, and Chinese. For each image, we have at least 5 captions in each language.
+
+In total we have 80,000 images which are downloaded automatically with the dataset.
+
+## Dataset Structure
+
+We show detailed information for all the configurations of the dataset.
+
+### Dataset Configurations
+
+We have 4 Configurations:
+
+#### artelingo
+
+- **Size of downloaded dataset files:** 23 GB
+- **Splits:** \['train', 'test', 'val'\]
+- **Number of Samples per splits:** \[920K, 94.1K, 46.9K\]
+
+#### dev
+
+- **Size of downloaded dataset files:** 3 GB
+- **Splits:** \['test', 'val'\]
+- **Number of Samples per splits:** \[94.1K, 46.9K\]
+
+#### wecia-emo
+
+Intended for the [WECIA](https://iccv23-wecia.github.io/) emotion prediction challenge. Instances does not have the emotion or the language attributes.
+- **Size of downloaded dataset files:** 1.2 GB
+- **Splits:** \['dev'\]
+- **Number of Samples per splits:** \[27.9K\]
+
+#### wecia-cap
+
+Intended for the [WECIA](https://iccv23-wecia.github.io/) affective caption generation challenge. Instances does not have the text.
+- **Size of downloaded dataset files:** 1.2 GB
+- **Splits:** \['dev'\]
+- **Number of Samples per splits:** \[16.3K\]
+
+### Data Fields
+The data fields are the same among all configs.
+
+- `uid`: a `int32` feature.
+- `image`: a `PIL.Image` feature
+- `art_style`: a `string` feature.
+- `paitning`: a `string` feature.
+- `emotion`: a `string` feature.
+- `language`: a `string` feature.
+- `text`: a `string` feature.
+
+## Dataset Creation
+
+### Curation Rationale
+ArtELingo is a benchmark and dataset designed to promote research on diversity
+across languages and cultures. It builds upon ArtEmis, a collection of 80,000 
+artworks from WikiArt with 450,000 emotion labels and English-only captions. 
+ArtELingo extends this dataset by adding 790,000 annotations in Arabic and 
+Chinese, as well as 4,800 annotations in Spanish, allowing for the evaluation
+of "cultural-transfer" performance in AI systems. With many artworks having 
+multiple annotations in three languages, the dataset enables the investigation
+of similarities and differences across linguistic and cultural contexts.
+Additionally, ArtELingo explores captioning tasks, demonstrating how diversity 
+in annotations can improve the performance of baseline AI models. The hope is 
+that ArtELingo will facilitate future research on multilinguality and 
+culturally-aware AI. The dataset is publicly available, including standard 
+splits and baseline models, to support and ease further research in this area.
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+ArtELingo uses images from the [wikiart dataset](https://www.wikiart.org/). 
+The images are mainly artworks since they are created with the intention to
+have an emotional impact on the viewer. ArtELingo assumes that WikiArt 
+is a representative sample of the cultures of interest. While WikiArt 
+is remarkably comprehensive, it has better coverage of the West than other 
+regions of the world based on WikiArt’s assignment of artworks to nationalities.
+
+The data was collected via Amazon Mechanical Turk, where only native speakers 
+were allowed to annotate the images. The English, Arabic, and Chinese subsets were 
+collected by 6377, 656, and 745 workers respectively. All workers were compensated
+with above minimal wage in each respective country. 
+
+#### Who are the source language producers?
+
+The data comes from Human annotators who natively speak each respective language.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+When using the ArtELingo dataset, researchers and developers must be mindful of 
+the potential social impact of the data. Emotions, cultural expressions, and 
+artistic representations can be sensitive topics, and AI systems trained on such 
+data may have implications on how they perceive and respond to users. It is 
+crucial to ensure that the dataset's usage does not perpetuate stereotypes or 
+biases related to specific cultures or languages. Ethical considerations should 
+be taken into account during the development and deployment of AI models trained 
+on ArtELingo to avoid any harmful consequences on individuals or communities.
+
+### Discussion of Biases
+
+ArtELingo was filtered against hate speech, racism, and obvious stereotypes. 
+However, Like any dataset, ArtELingo may contain inherent biases that could 
+influence the performance and behavior of AI systems. These biases could 
+arise from various sources, such as cultural differences in emotional 
+interpretations, variations in annotator perspectives, or imbalances in 
+the distribution of annotations across languages and cultures. Researchers 
+should be cautious about potential biases that might impact the dataset's 
+outcomes and address them appropriately. Transparently discussing and 
+documenting these biases is essential to facilitate a fair understanding of the 
+dataset's limitations and potential areas of improvement.
+
+
+## Additional Information
+
+### Dataset Curators
+
+The corpus was put together by [Youssef Mohamed](https://cemse.kaust.edu.sa/people/person/youssef-s-mohamed), 
+[Mohamed Abdelfattah](https://people.epfl.ch/mohamed.abdelfattah/?lang=en), 
+[Shyma Alhuwaider](https://cemse.kaust.edu.sa/aanslab/people/person/shyma-y-alhuwaider), 
+[Feifan Li](https://www.linkedin.com/in/feifan-li-3280a6249/),
+[Xiangliang Zhang](https://engineering.nd.edu/faculty/xiangliang-zhang/),
+[Kenneth Ward Church](https://www.khoury.northeastern.edu/people/kenneth-church/)
+and [Mohamed Elhoseiny](https://cemse.kaust.edu.sa/people/person/mohamed-elhoseiny).
+
+### Licensing Information
+
+Terms of Use: Before we are able to offer you access to the database, 
+please agree to the following terms of use. After approval, you (the 'Researcher') 
+receive permission to use the ArtELingo database (the 'Database') at King Abdullah 
+University of Science and Technology (KAUST). In exchange for being able to join the 
+ArtELingo community and receive such permission, Researcher hereby agrees to the 
+following terms and conditions:  [1.] The Researcher shall use the Database only for 
+non-commercial research and educational purposes.  [2.] The Universities make no 
+representations or warranties regarding the Database, including but not limited to 
+warranties of non-infringement or fitness for a particular purpose.  [3.] Researcher 
+accepts full responsibility for his or her use of the Database and shall defend and 
+indemnify the Universities, including their employees, Trustees, officers and agents, 
+against any and all claims arising from Researcher's use of the Database, and 
+Researcher's use of any copies of copyrighted 2D artworks originally uploaded to 
+http://www.wikiart.org that the Researcher may use in connection with the Database.  
+[4.] Researcher may provide research associates and colleagues with access to the 
+Database provided that they first agree to be bound by these terms and conditions. 
+[5.] The Universities reserve the right to terminate Researcher's access to the Database 
+at any time.  [6.] If Researcher is employed by a for-profit, commercial entity, 
+Researcher's employer shall also be bound by these terms and conditions, and Researcher 
+hereby represents that he or she is fully authorized to enter into this agreement on 
+behalf of such employer.  [7.] The international copyright laws shall apply to all 
+disputes under this agreement.
+
+### Citation Information
+
+```
+@inproceedings{mohamed2022artelingo,
+  title={ArtELingo: A Million Emotion Annotations of WikiArt with Emphasis on Diversity over Language and Culture},
+  author={Mohamed, Youssef and Abdelfattah, Mohamed and Alhuwaider, Shyma and Li, Feifan and Zhang, Xiangliang and Church, Kenneth and Elhoseiny, Mohamed},
+  booktitle={Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing},
+  pages={8770--8785},
+  year={2022}
+}
+```
+
+### Contributions
+
+Thanks to [@youssef101](https://github.com/Mo-youssef) for adding this dataset. [@Faizan](https://faixan-khan.github.io/) for testing.