README.md

---
task_categories:
- image-classification
tags:
- composition
---

# Dataset Card for CGQA dataset
This is the CGQA dataset from the [Learning Graph Embeddings for Compositional Zero-shot Learning](https://arxiv.org/abs/2102.01987) paper.


## Citation
If you use this dataset, please cite the following papers: 

```
@inproceedings{naeem2021learning,
  title={Learning graph embeddings for compositional zero-shot learning},
  author={Naeem, Muhammad Ferjad and Xian, Yongqin and Tombari, Federico and Akata, Zeynep},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={953--962},
  year={2021}
}
```

CGQA is derived from the GQA datset
```
@inproceedings{hudson2019gqa,
  title={Gqa: A new dataset for real-world visual reasoning and compositional question answering},
  author={Hudson, Drew A and Manning, Christopher D},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={6700--6709},
  year={2019}
}
```

The GQA dataset is derived from Visual Genome 
```
@article{krishna2017visual,
  title={Visual genome: Connecting language and vision using crowdsourced dense image annotations},
  author={Krishna, Ranjay and Zhu, Yuke and Groth, Oliver and Johnson, Justin and Hata, Kenji and Kravitz, Joshua and Chen, Stephanie and Kalantidis, Yannis and Li, Li-Jia and Shamma, David A and others},
  journal={International journal of computer vision},
  volume={123},
  number={1},
  pages={32--73},
  year={2017},
  publisher={Springer}
}
```

If you use this dataset with [compositional soft prompting](https://arxiv.org/abs/2204.03574), then cite this paper: 
```
@inproceedings{
  csp2023,
  title={Learning to Compose Soft Prompts for Compositional Zero-Shot Learning},
  author={Nihal V. Nayak and Peilin Yu and Stephen H. Bach},
  booktitle={International Conference on Learning Representations},
  year={2023}
}
```