COCO-FreeView is a laboratory-quality dataset of free viewing behavior. It contains the same natural images used in COCO-Search18, but labeled with 822,602 eye fixations from a free-viewing task.
10 university students participated in the data collection. The experiment procedure was modified from COCO-Search18, with no target being cued, no response being required from the participant, and the viewing time for each image being fixed to 5 seconds.
COCO-FreeView Dataset contains :
Image Stimuli: same images from COCO-Search18, download here
Eye Fixation: free-viewing fixations on all images
Training and validation set [Download]
Testing set [Download]
Readme file: details on the data format [Download]
Code on Github
If you use COCO-FreeView, please cite:
Chen, Y., Yang, Z., Chakraborty, S., Mondal, S., Ahn, S., Samaras, D., Hoai, M., & Zelinsky, G. (2022). Characterizing Target-Absent Human Attention. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (pp. 5031-5040).
Yang, Z., Mondal, S., Ahn, S., Zelinsky, G., Hoai, M., & Samaras, D. (2023). Predicting Human Attention using Computational Attention. arXiv preprint arXiv:2303.09383.
@inproceedings{chen2022characterizing,
title={Characterizing Target-Absent Human Attention},
author={Chen, Yupei and Yang, Zhibo and Chakraborty, Souradeep and Mondal, Sounak and Ahn, Seoyoung and Samaras, Dimitris and Hoai, Minh and Zelinsky, Gregory},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
pages={5031--5040},
year={2022}
}
@article{yang2023predicting,
title={Predicting Human Attention using Computational Attention},
author={Yang, Zhibo and Mondal, Sounak and Ahn, Seoyoung and Zelinsky, Gregory and Hoai, Minh and Samaras, Dimitris},
journal={arXiv preprint arXiv:2303.09383},
year={2023}
}