Beyond Universal Saliency: Personalized Saliency Prediction with Multi-task CNN

Yanyu Xu, Nianyi Li, Junru Wu, Jingyi Yu, Shenghua Gao
2017 Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence  
Saliency detection is a long standing problem in computer vision. Tremendous efforts have been focused on exploring a universal saliency model across users despite their differences in gender, race, age, etc. Yet recent psychology studies suggest that saliency is highly specific than universal: individuals exhibit heterogeneous gaze patterns when viewing an identical scene containing multiple salient objects. In this paper, we first show that such heterogeneity is common and critical for
more » ... e saliency prediction. Our study also produces the first database of personalized saliency maps (PSMs). We model PSM based on universal saliency map (USM) shared by different participants and adopt a multi-task CNN framework to estimate the discrepancy between PSM and USM. Comprehensive experiments demonstrate that our new PSM model and prediction scheme are effective and reliable.
doi:10.24963/ijcai.2017/543 dblp:conf/ijcai/XuLWYG17 fatcat:6aw6om2k4rc2pczilbnycqvtly