Abstract

In this paper, we tackle the problem of saliency-guided image manipulation for adjusting the saliency distribution over image regions. Conventional approaches ordinarily utilize explicit operations on altering the low-level features based on the selected saliency computation. However, it is difficult to generalize such methods for various saliency estimations. To address this issue, we propose a deep learning-based model that bridges between any differentiable saliency estimation methods and a neural network which applies image manipulation. Thus, the manipulation is directly optimized in order to satisfy saliency-guidance. Extensive experiments verify the capacity of our model in saliency-driven image editing and show favorable performance against numerous baselines.

Introduction Video

BMVC 2019 Poster

BMVC 2019 Paper

 
@inproceedings{chen19bmvc,
 title = {Guide Your Eyes: Learning Image Manipulation under Saliency Guidance},
 author = {Yen-Chung Chen and Keng-Jui Chang and Yu-Chiang Frank Wang and Yi-Hsuan Tsai and Wei-Chen Chiu},
 booktitle = {British Machine Vision Conference (BMVC)},
 year = {2019}
}