StyleMM: Stylized 3D Morphable Face Model via Text‐Driven Aligned Image Translation.
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| Title: | StyleMM: Stylized 3D Morphable Face Model via Text‐Driven Aligned Image Translation. |
|---|---|
| Authors: | Lee, Seungmi1 (AUTHOR), Yun, Kwan1 (AUTHOR), Noh, Junyong1 (AUTHOR) |
| Source: | Computer Graphics Forum. Oct2025, Vol. 44 Issue 7, p1-15. 15p. |
| Subjects: | Three-dimensional modeling, Morphing (Computer animation), Generative artificial intelligence, Image converters |
| Abstract: | We introduce StyleMM, a novel framework that can construct a stylized 3D Morphable Model (3DMM) based on user‐defined text descriptions specifying a target style. Building upon a pre‐trained mesh deformation network and a texture generator for original 3DMM‐based realistic human faces, our approach fine‐tunes these models using stylized facial images generated via text‐guided image‐to‐image (i2i) translation with a diffusion model, which serve as stylization targets for the rendered mesh. To prevent undesired changes in identity, facial alignment, or expressions during i2i translation, we introduce a stylization method that explicitly preserves the facial attributes of the source image. By maintaining these critical attributes during image stylization, the proposed approach ensures consistent 3D style transfer across the 3DMM parameter space through image‐based training. Once trained, StyleMM enables feed‐forward generation of stylized face meshes with explicit control over shape, expression, and texture parameters, producing meshes with consistent vertex connectivity and animatability. Quantitative and qualitative evaluations demonstrate that our approach outperforms state‐of‐the‐art methods in terms of identity‐level facial diversity and stylization capability. The code and videos are available at kwanyun.github.io/stylemm_page. Categories and Subject Descriptors (according to ACM CCS): I.3.6 [Computer Graphics]: Methodology and Techniques— [ABSTRACT FROM AUTHOR] |
| Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 188721017 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: StyleMM: Stylized 3D Morphable Face Model via Text‐Driven Aligned Image Translation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Lee%2C+Seungmi%22">Lee, Seungmi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yun%2C+Kwan%22">Yun, Kwan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Noh%2C+Junyong%22">Noh, Junyong</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Computer+Graphics+Forum%22">Computer Graphics Forum</searchLink>. Oct2025, Vol. 44 Issue 7, p1-15. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Three-dimensional+modeling%22">Three-dimensional modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Morphing+%28Computer+animation%29%22">Morphing (Computer animation)</searchLink><br /><searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Image+converters%22">Image converters</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: We introduce StyleMM, a novel framework that can construct a stylized 3D Morphable Model (3DMM) based on user‐defined text descriptions specifying a target style. Building upon a pre‐trained mesh deformation network and a texture generator for original 3DMM‐based realistic human faces, our approach fine‐tunes these models using stylized facial images generated via text‐guided image‐to‐image (i2i) translation with a diffusion model, which serve as stylization targets for the rendered mesh. To prevent undesired changes in identity, facial alignment, or expressions during i2i translation, we introduce a stylization method that explicitly preserves the facial attributes of the source image. By maintaining these critical attributes during image stylization, the proposed approach ensures consistent 3D style transfer across the 3DMM parameter space through image‐based training. Once trained, StyleMM enables feed‐forward generation of stylized face meshes with explicit control over shape, expression, and texture parameters, producing meshes with consistent vertex connectivity and animatability. Quantitative and qualitative evaluations demonstrate that our approach outperforms state‐of‐the‐art methods in terms of identity‐level facial diversity and stylization capability. The code and videos are available at kwanyun.github.io/stylemm_page. Categories and Subject Descriptors (according to ACM CCS): I.3.6 [Computer Graphics]: Methodology and Techniques— [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/cgf.70234 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 1 Subjects: – SubjectFull: Three-dimensional modeling Type: general – SubjectFull: Morphing (Computer animation) Type: general – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Image converters Type: general Titles: – TitleFull: StyleMM: Stylized 3D Morphable Face Model via Text‐Driven Aligned Image Translation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Lee, Seungmi – PersonEntity: Name: NameFull: Yun, Kwan – PersonEntity: Name: NameFull: Noh, Junyong IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 01677055 Numbering: – Type: volume Value: 44 – Type: issue Value: 7 Titles: – TitleFull: Computer Graphics Forum Type: main |
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