{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T14:45:13Z","timestamp":1767624313042,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":46,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,7,13]],"date-time":"2024-07-13T00:00:00Z","timestamp":1720828800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,7,13]]},"DOI":"10.1145\/3641519.3657451","type":"proceedings-article","created":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T10:39:28Z","timestamp":1720780768000},"page":"1-11","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["QT-Font: High-efficiency Font Synthesis via Quadtree-based Diffusion Models"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-6201-7767","authenticated-orcid":false,"given":"Yitian","family":"Liu","sequence":"first","affiliation":[{"name":"Wangxuan Institute of Computer Technology, Peking University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2683-7170","authenticated-orcid":false,"given":"Zhouhui","family":"Lian","sequence":"additional","affiliation":[{"name":"Wangxuan Institute of Computer Technology, Peking University, China"}]}],"member":"320","published-online":{"date-parts":[[2024,7,13]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"International conference on machine learning. PMLR, 40\u201349","author":"Achlioptas Panos","year":"2018","unstructured":"Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas. 2018. Learning representations and generative models for 3d point clouds. In International conference on machine learning. PMLR, 40\u201349."},{"key":"e_1_3_2_2_2_1","volume-title":"SVG Vector Font Generation for Chinese Characters with Transformer. arXiv preprint arXiv:2206.10329","author":"Aoki Haruka","year":"2022","unstructured":"Haruka Aoki and Kiyoharu Aizawa. 2022. SVG Vector Font Generation for Chinese Characters with Transformer. arXiv preprint arXiv:2206.10329 (2022)."},{"key":"e_1_3_2_2_3_1","first-page":"17981","article-title":"Structured denoising diffusion models in discrete state-spaces","volume":"34","author":"Austin Jacob","year":"2021","unstructured":"Jacob Austin, Daniel\u00a0D Johnson, Jonathan Ho, Daniel Tarlow, and Rianne Van Den\u00a0Berg. 2021. Structured denoising diffusion models in discrete state-spaces. Advances in Neural Information Processing Systems 34 (2021), 17981\u201317993.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"crossref","unstructured":"Samaneh Azadi Matthew Fisher Vladimir\u00a0G Kim Zhaowen Wang Eli Shechtman and Trevor Darrell. 2018. Multi-content gan for few-shot font style transfer. In CVPR. 7564\u20137573.","DOI":"10.1109\/CVPR.2018.00789"},{"key":"e_1_3_2_2_5_1","first-page":"16351","article-title":"Deepsvg: A hierarchical generative network for vector graphics animation","volume":"33","author":"Carlier Alexandre","year":"2020","unstructured":"Alexandre Carlier, Martin Danelljan, Alexandre Alahi, and Radu Timofte. 2020. Deepsvg: A hierarchical generative network for vector graphics animation. Advances in Neural Information Processing Systems 33 (2020), 16351\u201316361.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00510"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00012"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00609"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00011"},{"key":"e_1_3_2_2_10_1","volume-title":"Diffusion models beat gans on image synthesis. Advances in neural information processing systems 34","author":"Dhariwal Prafulla","year":"2021","unstructured":"Prafulla Dhariwal and Alexander Nichol. 2021. Diffusion models beat gans on image synthesis. Advances in neural information processing systems 34 (2021), 8780\u20138794."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3355089.3356574"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1281500.1281665"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01043"},{"key":"e_1_3_2_2_14_1","volume-title":"Diff-Font: Diffusion Model for Robust One-Shot Font Generation. arXiv preprint arXiv:2212.05895","author":"He Haibin","year":"2022","unstructured":"Haibin He, Xinyuan Chen, Chaoyue Wang, Juhua Liu, Bo Du, Dacheng Tao, and Yu Qiao. 2022. Diff-Font: Diffusion Model for Robust One-Shot Font Generation. arXiv preprint arXiv:2212.05895 (2022)."},{"key":"e_1_3_2_2_15_1","volume-title":"Denoising diffusion probabilistic models. Advances in neural information processing systems 33","author":"Ho Jonathan","year":"2020","unstructured":"Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising diffusion probabilistic models. Advances in neural information processing systems 33 (2020), 6840\u20136851."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58539-6_10"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"crossref","unstructured":"Yue Jiang Zhouhui Lian Yingmin Tang and Jianguo Xiao. 2017. DCFont: an end-to-end deep Chinese font generation system. In SIGGRAPH Asia. ACM 22.","DOI":"10.1145\/3145749.3149440"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01312"},{"volume-title":"Computer Graphics Forum","author":"Lian Zhouhui","key":"e_1_3_2_2_19_1","unstructured":"Zhouhui Lian and Yichen Gao. 2022. CVFont: Synthesizing Chinese Vector Fonts via Deep Layout Inferring. In Computer Graphics Forum. Wiley Online Library."},{"key":"e_1_3_2_2_20_1","volume-title":"CalliPaint: Chinese Calligraphy Inpainting with Diffusion Model. arXiv preprint arXiv:2312.01536","author":"Liao Qisheng","year":"2023","unstructured":"Qisheng Liao, Zhinuo Wang, Muhammad Abdul-Mageed, and Gus Xia. 2023. CalliPaint: Chinese Calligraphy Inpainting with Diffusion Model. arXiv preprint arXiv:2312.01536 (2023)."},{"key":"e_1_3_2_2_21_1","volume-title":"DeepCalliFont: Few-shot Chinese Calligraphy Font Synthesis by Integrating Dual-modality Generative Models. arXiv preprint arXiv:2312.10314","author":"Liu Yitian","year":"2023","unstructured":"Yitian Liu and Zhouhui Lian. 2023. DeepCalliFont: Few-shot Chinese Calligraphy Font Synthesis by Integrating Dual-modality Generative Models. arXiv preprint arXiv:2312.10314 (2023)."},{"key":"e_1_3_2_2_22_1","volume-title":"Learning implicit glyph shape representation","author":"Liu Ying-Tian","year":"2022","unstructured":"Ying-Tian Liu, Yuan-Chen Guo, Yi-Xiao Li, Chen Wang, and Song-Hai Zhang. 2022. Learning implicit glyph shape representation. IEEE Transactions on Visualization and Computer Graphics (2022)."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00802"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDAR.2017.181"},{"key":"e_1_3_2_2_25_1","volume-title":"Point-e: A system for generating 3d point clouds from complex prompts. arXiv preprint arXiv:2212.08751","author":"Nichol Alex","year":"2022","unstructured":"Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, and Mark Chen. 2022. Point-e: A system for generating 3d point clouds from complex prompts. arXiv preprint arXiv:2212.08751 (2022)."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01787"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00025"},{"key":"e_1_3_2_2_28_1","volume-title":"Few-shot Font Generation with Localized Style Representations and Factorization. arXiv preprint arXiv:2009.11042","author":"Park Song","year":"2020","unstructured":"Song Park, Sanghyuk Chun, Junbum Cha, Bado Lee, and Hyunjung Shim. 2020. Few-shot Font Generation with Localized Style Representations and Factorization. arXiv preprint arXiv:2009.11042 (2020)."},{"key":"e_1_3_2_2_29_1","volume-title":"Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts. arXiv preprint arXiv:2104.00887","author":"Park Song","year":"2021","unstructured":"Song Park, Sanghyuk Chun, Junbum Cha, Bado Lee, and Hyunjung Shim. 2021. Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts. arXiv preprint arXiv:2104.00887 (2021)."},{"key":"e_1_3_2_2_30_1","first-page":"12637","article-title":"A multi-implicit neural representation for fonts","volume":"34","author":"Reddy Pradyumna","year":"2021","unstructured":"Pradyumna Reddy, Zhifei Zhang, Zhaowen Wang, Matthew Fisher, Hailin Jin, and Niloy Mitra. 2021. A multi-implicit neural representation for fonts. Advances in Neural Information Processing Systems 34 (2021), 12637\u201312647.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"e_1_3_2_2_32_1","volume-title":"Learning to write stylized chinese characters by reading a handful of examples. arXiv preprint arXiv:1712.06424","author":"Sun Danyang","year":"2017","unstructured":"Danyang Sun, Tongzheng Ren, Chongxun Li, Hang Su, and Jun Zhu. 2017. Learning to write stylized chinese characters by reading a handful of examples. arXiv preprint arXiv:1712.06424 (2017)."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00774"},{"key":"e_1_3_2_2_34_1","first-page":"2017","article-title":"zi2zi: Master chinese calligraphy with conditional adversarial networks, 2017","volume":"3","author":"Tian Yuchen","year":"2017","unstructured":"Yuchen Tian. 2017. zi2zi: Master chinese calligraphy with conditional adversarial networks, 2017. Retrieved Jun 3 (2017), 2017.","journal-title":"Retrieved Jun"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00185"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3072959.3073608","article-title":"O-cnn: Octree-based convolutional neural networks for 3d shape analysis","volume":"36","author":"Wang Peng-Shuai","year":"2017","unstructured":"Peng-Shuai Wang, Yang Liu, Yu-Xiao Guo, Chun-Yu Sun, and Xin Tong. 2017. O-cnn: Octree-based convolutional neural networks for 3d shape analysis. ACM Transactions On Graphics (TOG) 36, 4 (2017), 1\u201311.","journal-title":"ACM Transactions On Graphics (TOG)"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3528223.3530087"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3478513.3480488","article-title":"DeepVecFont: synthesizing high-quality vector fonts via dual-modality learning","volume":"40","author":"Wang Yizhi","year":"2021","unstructured":"Yizhi Wang and Zhouhui Lian. 2021. DeepVecFont: synthesizing high-quality vector fonts via dual-modality learning. ACM Transactions on Graphics (TOG) 40, 6 (2021), 1\u201315.","journal-title":"ACM Transactions on Graphics (TOG)"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/130881.130882"},{"key":"e_1_3_2_2_40_1","volume-title":"Calligan: Style and structure-aware chinese calligraphy character generator. arXiv preprint arXiv:2005.12500","author":"Wu Shan-Jean","year":"2020","unstructured":"Shan-Jean Wu, Chih-Yuan Yang, and Jane Yung-jen Hsu. 2020. Calligan: Style and structure-aware chinese calligraphy character generator. arXiv preprint arXiv:2005.12500 (2020)."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00184"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00509"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00464"},{"key":"e_1_3_2_2_44_1","volume-title":"FontDiffuser: One-Shot Font Generation via Denoising Diffusion with Multi-Scale Content Aggregation and Style Contrastive Learning. arXiv preprint arXiv:2312.12142","author":"Yang Zhenhua","year":"2023","unstructured":"Zhenhua Yang, Dezhi Peng, Yuxin Kong, Yuyi Zhang, Cong Yao, and Lianwen Jin. 2023. FontDiffuser: One-Shot Font Generation via Denoising Diffusion with Multi-Scale Content Aggregation and Style Contrastive Learning. arXiv preprint arXiv:2312.12142 (2023)."},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i4.16438"},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"crossref","unstructured":"Yexun Zhang Ya Zhang and Wenbin Cai. 2018. Separating style and content for generalized style transfer. In CVPR. 8447\u20138455.","DOI":"10.1109\/CVPR.2018.00881"}],"event":{"name":"SIGGRAPH '24: Special Interest Group on Computer Graphics and Interactive Techniques Conference","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques"],"location":"Denver CO USA","acronym":"SIGGRAPH '24"},"container-title":["Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3641519.3657451","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3641519.3657451","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:09:36Z","timestamp":1750295376000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3641519.3657451"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,13]]},"references-count":46,"alternative-id":["10.1145\/3641519.3657451","10.1145\/3641519"],"URL":"https:\/\/doi.org\/10.1145\/3641519.3657451","relation":{},"subject":[],"published":{"date-parts":[[2024,7,13]]},"assertion":[{"value":"2024-07-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}