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-theart exemplar-based methods to improve their robustness with ignorable computational cost.
| Original language | English |
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| Title of host publication | Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) |
| Editors | Carles Sierra |
| Publisher | International Joint Conferences on Artificial Intelligence |
| Pages | 4530-4536 |
| ISBN (Electronic) | 9780999241103 |
| DOIs | |
| Publication status | Published - Aug 2017 |
| Event | 26th International Joint Conference on Artificial Intelligence (IJCAI 2017) - Melbourne, Australia Duration: 19 Aug 2017 → 25 Aug 2017 https://www.ijcai.org/proceedings/2017/ |
Publication series
| Name | |
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| ISSN (Print) | 1045-0823 |
Conference
| Conference | 26th International Joint Conference on Artificial Intelligence (IJCAI 2017) |
|---|---|
| Place | Australia |
| City | Melbourne |
| Period | 19/08/17 → 25/08/17 |
| Internet address |
Bibliographical note
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