ARtVista: Gateway To Empower Anyone Into Artist
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866929276008267776 |
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| author | Hoang, Trong-Vu Nguyen, Quang-Binh Ly, Duy-Nam Le, Khanh-Duy Nguyen, Tam V. Tran, Minh-Triet Le, Trung-Nghia |
| author_facet | Hoang, Trong-Vu Nguyen, Quang-Binh Ly, Duy-Nam Le, Khanh-Duy Nguyen, Tam V. Tran, Minh-Triet Le, Trung-Nghia |
| contents | Drawing is an art that enables people to express their imagination and emotions. However, individuals usually face challenges in drawing, especially when translating conceptual ideas into visually coherent representations and bridging the gap between mental visualization and practical execution. In response, we propose ARtVista - a novel system integrating AR and generative AI technologies. ARtVista not only recommends reference images aligned with users' abstract ideas and generates sketches for users to draw but also goes beyond, crafting vibrant paintings in various painting styles. ARtVista also offers users an alternative approach to create striking paintings by simulating the paint-by-number concept on reference images, empowering users to create visually stunning artwork devoid of the necessity for advanced drawing skills. We perform a pilot study and reveal positive feedback on its usability, emphasizing its effectiveness in visualizing user ideas and aiding the painting process to achieve stunning pictures without requiring advanced drawing skills. The source code will be available at https://github.com/htrvu/ARtVista. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_08876 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ARtVista: Gateway To Empower Anyone Into Artist Hoang, Trong-Vu Nguyen, Quang-Binh Ly, Duy-Nam Le, Khanh-Duy Nguyen, Tam V. Tran, Minh-Triet Le, Trung-Nghia Computer Vision and Pattern Recognition Drawing is an art that enables people to express their imagination and emotions. However, individuals usually face challenges in drawing, especially when translating conceptual ideas into visually coherent representations and bridging the gap between mental visualization and practical execution. In response, we propose ARtVista - a novel system integrating AR and generative AI technologies. ARtVista not only recommends reference images aligned with users' abstract ideas and generates sketches for users to draw but also goes beyond, crafting vibrant paintings in various painting styles. ARtVista also offers users an alternative approach to create striking paintings by simulating the paint-by-number concept on reference images, empowering users to create visually stunning artwork devoid of the necessity for advanced drawing skills. We perform a pilot study and reveal positive feedback on its usability, emphasizing its effectiveness in visualizing user ideas and aiding the painting process to achieve stunning pictures without requiring advanced drawing skills. The source code will be available at https://github.com/htrvu/ARtVista. |
| title | ARtVista: Gateway To Empower Anyone Into Artist |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2403.08876 |