Although images from MSRA-1000 have a large variety in their content, background structures are primarily simple and smooth. To represent the situations that natural images generally fall into, we extend our Complex Scene Saliency Dataset (CSSD) in a larger dataset (ECSSD) with 1000 images, which includes many semantically meaningful but structurally complex images for evaluation. The images are acquired from the internet and 5 helpers were asked to produce the ground truth masks. Several examples with their corresponding masks are shown above.
@inproceedings{yan2013hierarchical,
title={Hierarchical saliency detection},
author={Yan, Qiong and Xu, Li and Shi, Jianping and Jia, Jiaya},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={1155--1162},
year={2013}
}