Learning to Trace: Expressive Line Drawing Generation from Photographs
| dc.contributor.author | Inoue, Naoto | en_US |
| dc.contributor.author | Ito, Daichi | en_US |
| dc.contributor.author | Xu, Ning | en_US |
| dc.contributor.author | Yang, Jimei | en_US |
| dc.contributor.author | Price, Brian | en_US |
| dc.contributor.author | Yamasaki, Toshihiko | en_US |
| dc.contributor.editor | Lee, Jehee and Theobalt, Christian and Wetzstein, Gordon | en_US |
| dc.date.accessioned | 2019-10-14T05:06:38Z | |
| dc.date.available | 2019-10-14T05:06:38Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | In this paper, we present a new computational method for automatically tracing high-resolution photographs to create expressive line drawings. We define expressive lines as those that convey important edges, shape contours, and large-scale texture lines that are necessary to accurately depict the overall structure of objects (similar to those found in technical drawings) while still being sparse and artistically pleasing. Given a photograph, our algorithm extracts expressive edges and creates a clean line drawing using a convolutional neural network (CNN). We employ an end-to-end trainable fully-convolutional CNN to learn the model in a data-driven manner. The model consists of two networks to cope with two sub-tasks; extracting coarse lines and refining them to be more clean and expressive. To build a model that is optimal for each domain, we construct two new datasets for face/body and manga background. The experimental results qualitatively and quantitatively demonstrate the effectiveness of our model. We further illustrate two practical applications. | en_US |
| dc.description.number | 7 | |
| dc.description.sectionheaders | Lines and Sketches | |
| dc.description.seriesinformation | Computer Graphics Forum | |
| dc.description.volume | 38 | |
| dc.identifier.doi | 10.1111/cgf.13817 | |
| dc.identifier.issn | 1467-8659 | |
| dc.identifier.pages | 69-80 | |
| dc.identifier.uri | https://doi.org/10.1111/cgf.13817 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.1111/cgf13817 | |
| dc.publisher | The Eurographics Association and John Wiley & Sons Ltd. | en_US |
| dc.subject | Computing methodologies | |
| dc.subject | Image manipulation | |
| dc.subject | Applied computing | |
| dc.subject | Fine arts | |
| dc.title | Learning to Trace: Expressive Line Drawing Generation from Photographs | en_US |