PLDGAN: portrait line drawing generation with prior knowledge and conditioning target
文献类型：期刊论文
| 作者 | Li, Sifei1,2; Wu, Fuzhang4; Fan, Yuqing4 ; Song, Xue3; Dong, Weiming1,2
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| 刊名 | VISUAL COMPUTER
 |
| 出版日期 | 2023-06-24 |
| 页码 | 12 |
| 关键词 | Portrait line drawings Artistic stylization Conditional generative adversarial networks |
| ISSN号 | 0178-2789 |
| DOI | 10.1007/s00371-023-02956-1 |
| 通讯作者 | Wu, Fuzhang(wfz275@126.com) |
| 英文摘要 | Line drawing, a form of minimalist art, is highly abstract and expressive with practical use in conveying 3D shapes and indicating object occlusion. Generating line drawings from photographs is a challenging task that requires the compression of rich texture information into sparse geometric elements, such as lines, curves, and circles, without compromising semantic information. Furthermore, a portrait line drawing should include a full human silhouette and important semantic lines of scenes while avoiding messy lines. To address those challenges, we propose a novel method for generating portrait line drawings, named PLDGAN (Portrait Line Drawing Generative Adversarial Network), which utilizes prior knowledge of pose and semantic segmentation information. We also design a conditioning target and adjust the content loss to the original target loss. To train our PLDGAN, we collect a new dataset containing pairwise portrait images and professional portrait line drawings. Our experiments show that our proposed method achieves state-of-the-art performance and can generate high-quality portrait line drawings. |
| WOS关键词 | IMAGE TRANSLATION ; EDGE-DETECTION ; RESOLUTION |
| 资助项目 | National Key Ramp;D Program of China[2020AAA0106200] ; National Natural~Science Foundation of China[61832016] ; National Natural~Science Foundation of China[U20B2070] ; Beijing Natural Science Foundation[L221013] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001019834000001 |
| 出版者 | SPRINGER |
| 资助机构 | National Key Ramp;D Program of China ; National Natural~Science Foundation of China ; Beijing Natural Science Foundation |
| 源URL | [http://ir.ia.ac.cn/handle/173211/53603]  |
| 专题 | 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Wu, Fuzhang |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, MAIS, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 3.Zhengzhou Univ, Zhengzhou, Peoples R China 4.Chinese Acad Sci, Inst Software, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Sifei,Wu, Fuzhang,Fan, Yuqing,et al. PLDGAN: portrait line drawing generation with prior knowledge and conditioning target[J]. VISUAL COMPUTER,2023:12. |
| APA | Li, Sifei,Wu, Fuzhang,Fan, Yuqing,Song, Xue,&Dong, Weiming.(2023).PLDGAN: portrait line drawing generation with prior knowledge and conditioning target.VISUAL COMPUTER,12. |
| MLA | Li, Sifei,et al."PLDGAN: portrait line drawing generation with prior knowledge and conditioning target".VISUAL COMPUTER (2023):12. |
入库方式： OAI收割
来源：自动化研究所
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