Adaptively-Realistic Image Generation from Stroke and Sketch with Diffusion Model

Shin I. Cheng*, Yu Jie Chen, Wei Chen Chiu, Hung Yu Tseng, Hsin Ying Lee

*此作品的通信作者

研究成果: Conference contribution同行評審

15 引文 斯高帕斯(Scopus)

摘要

Generating images from hand-drawings is a crucial and fundamental task in content creation. The translation is difficult as there exist infinite possibilities and the different users usually expect different outcomes. Therefore, we propose a unified framework supporting a three-dimensional control over the image synthesis from sketches and strokes based on diffusion models. Users can not only decide the level of faithfulness to the input strokes and sketches, but also the degree of realism, as the user inputs are usually not consistent with the real images. Qualitative and quantitative experiments demonstrate that our framework achieves state-of-the-art performance while providing flexibility in generating customized images with control over shape, color, and realism. Moreover, our method unleashes applications such as editing on real images, generation with partial sketches and strokes, and multi-domain multi-modal synthesis.

原文English
主出版物標題Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023
發行者Institute of Electrical and Electronics Engineers Inc.
頁面4043-4051
頁數9
ISBN(電子)9781665493468
DOIs
出版狀態Published - 2023
事件23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023 - Waikoloa, United States
持續時間: 3 1月 20237 1月 2023

出版系列

名字Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023

Conference

Conference23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023
國家/地區United States
城市Waikoloa
期間3/01/237/01/23

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