Artist-Inator: Text-based, Gloss-aware Non-photorealistic Stylization
| dc.contributor.author | Subias, Jose Daniel | en_US |
| dc.contributor.author | Daniel-Soriano, Saúl | en_US |
| dc.contributor.author | Gutierrez, Diego | en_US |
| dc.contributor.author | Serrano, Ana | en_US |
| dc.contributor.editor | Wang, Beibei | en_US |
| dc.contributor.editor | Wilkie, Alexander | en_US |
| dc.date.accessioned | 2025-06-20T07:55:54Z | |
| dc.date.available | 2025-06-20T07:55:54Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Large diffusion models have made a remarkable leap synthesizing high-quality artistic images from text descriptions. However, these powerful pre-trained models still lack control to guide key material appearance properties, such as gloss. In this work, we present a threefold contribution: (1) we analyze how gloss is perceived across different artistic styles (i.e., oil painting, watercolor, ink pen, charcoal, and soft crayon); (2) we leverage our findings to create a dataset with 1,336,272 stylized images of many different geometries in all five styles, including automatically-computed text descriptions of their appearance (e.g., ''A glossy bunny hand painted with an orange soft crayon''); and (3) we train ControlNet to condition Stable Diffusion XL synthesizing novel painterly depictions of new objects, using simple inputs such as edge maps, hand-drawn sketches, or clip arts. Compared to previous approaches, our framework yields more accurate results despite the simplified input, as we show both quantitative and qualitatively. | en_US |
| dc.description.number | 4 | |
| dc.description.sectionheaders | Stylization and Image Processing | |
| dc.description.seriesinformation | Computer Graphics Forum | |
| dc.description.volume | 44 | |
| dc.identifier.doi | 10.1111/cgf.70182 | |
| dc.identifier.issn | 1467-8659 | |
| dc.identifier.pages | 15 pages | |
| dc.identifier.uri | https://doi.org/10.1111/cgf.70182 | |
| dc.identifier.uri | https://diglib.eg.org/handle/10.1111/cgf70182 | |
| dc.publisher | The Eurographics Association and John Wiley & Sons Ltd. | en_US |
| dc.rights | Attribution 4.0 International License | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | CCS Concepts: Computing methodologies → Non-photorealistic rendering; Image processing; Perception | |
| dc.subject | Computing methodologies → Non | |
| dc.subject | photorealistic rendering | |
| dc.subject | Image processing | |
| dc.subject | Perception | |
| dc.title | Artist-Inator: Text-based, Gloss-aware Non-photorealistic Stylization | en_US |