Fast Preprocessing for Robust Face Sketch Synthesis
Abstract
Exemplar-based face sketch synthesis methods usually meet the challenging problem that input photos are captured in different lighting conditions from training photos. The critical step causing the failure is the search of similar patch candidates for an input photo patch. Conventional illumination invariant patch distances are adopted rather than directly relying on pixel intensity difference, but they will fail when local contrast within a patch changes. In this paper, we propose a fast preprocessing method named Bidirectional Luminance Remapping (BLR), which interactively adjust the lighting of training and input photos. Our method can be directly integrated into state-of-the-art exemplar-based methods to improve their robustness with ignorable computational cost
Cite
Text
Song et al. "Fast Preprocessing for Robust Face Sketch Synthesis." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/632Markdown
[Song et al. "Fast Preprocessing for Robust Face Sketch Synthesis." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/song2017ijcai-fast/) doi:10.24963/IJCAI.2017/632BibTeX
@inproceedings{song2017ijcai-fast,
title = {{Fast Preprocessing for Robust Face Sketch Synthesis}},
author = {Song, Yibing and Zhang, Jiawei and Bao, Linchao and Yang, Qingxiong},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2017},
pages = {4530-4536},
doi = {10.24963/IJCAI.2017/632},
url = {https://mlanthology.org/ijcai/2017/song2017ijcai-fast/}
}