Overview
The MSRA Salient Object Database, which originally provides salient object annotation in terms of bounding boxes provided by 3-9 users, is widely used in salient object detection and segmentation community.
Data Collection
The MSRA10K benchmark dataset (a.k.a. THUS10000) comprises of per-pixel ground truth annotation for 10, 000 MSRA images (181 MB), each of which has an unambiguous salient object and the object region is accurately annotated with pixel wise ground-truth labeling (13.1M). We provide saliency maps (5.3 GB containing 170, 000 image) for our methods as well as other 15 state of the art methods, including FT [1], AIM [2], MSS [3], SEG [4], SeR [5], SUN [6], SWD [7], IM [8], IT [9], GB [10], SR [11], CA [12], LC [13], AC [14], and CB [15]. Saliency segmentation (71.3MB) results for FT[1], SEG[4], and CB[10] are also available.
Citation
@article{ChengPAMI,
author = {Ming-Ming Cheng and Niloy J. Mitra and Xiaolei Huang and Philip H. S. Torr and
Shi-Min Hu},
title = {Global Contrast based Salient Region Detection},
year = {2015},
journal= {IEEE TPAMI},
volume={37},
number={3},
pages={569--582},
doi = {10.1109/TPAMI.2014.2345401},
}
@conference{13iccv/Cheng_Saliency,
title={Efficient Salient Region Detection with Soft Image Abstraction},
author={Ming-Ming Cheng and Jonathan Warrell and Wen-Yan Lin and Shuai Zheng
and Vibhav Vineet and Nigel Crook},
booktitle={IEEE ICCV},
pages={1529--1536},
year={2013},
}
@article{SalObjSurvey,
author = {Ali Borji and Ming-Ming Cheng and Huaizu Jiang and Jia Li},
title = {Salient Object Detection: A Survey},
journal = {ArXiv e-prints},
archivePrefix = {arXiv},
eprint = {arXiv:1411.5878},
year = {2014},
}
@article{SalObjBenchmark,
author = {Ali Borji and Ming-Ming Cheng and Huaizu Jiang and Jia Li},
title = {Salient Object Detection: A Benchmark},
journal = {IEEE TIP},
year={2015},
volume={24},
number={12},
pages={5706-5722},
doi={10.1109/TIP.2015.2487833},
}