Learning to Blend Photos
Abstract
Photo blending is a common technique to create aesthetically pleasing artworks by combining multiple photos. However, the process of photo blending is usually time-consuming, and care must be taken in the process of blending, filtering, positioning, and masking each of the source photos. To make photo blending accessible to general public, we propose an efficient approach for automatic photo blending via deep learning. Specifically, given a foreground image and a background image, our proposed method automatically generates a set of blending photos with scores that indicate the aesthetics quality with the proposed quality network and policy network. Experimental results show that the proposed approach can effectively generate high quality blending photos with efficiency.
Cite
Text
Hung et al. "Learning to Blend Photos." Proceedings of the European Conference on Computer Vision (ECCV), 2018. doi:10.1007/978-3-030-01234-2_5Markdown
[Hung et al. "Learning to Blend Photos." Proceedings of the European Conference on Computer Vision (ECCV), 2018.](https://mlanthology.org/eccv/2018/hung2018eccv-learning/) doi:10.1007/978-3-030-01234-2_5BibTeX
@inproceedings{hung2018eccv-learning,
title = {{Learning to Blend Photos}},
author = {Hung, Wei-Chih and Zhang, Jianming and Shen, Xiaohui and Lin, Zhe and Lee, Joon-Young and Yang, Ming-Hsuan},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2018},
doi = {10.1007/978-3-030-01234-2_5},
url = {https://mlanthology.org/eccv/2018/hung2018eccv-learning/}
}