T2C: Text-guided 4D Cloth Generation

In the age of AIGC, the creation process is increasingly automated. Generating vivid characters with clothing and motions according to scripts or novels is no exception. Unfortunately, the diversity of fabric topologies, the complexity of fabric layering, and the flexibility of fabric motion make most approaches only applicable to motion generation for characters in undressing or tight-fitting clothing. This article introduces a novel approach named T2C , which employs a multi-layered clothing representation and a physics-based clothing animation paradigm to generate text-controlled Clothed 4D Humans, expanding the boundaries of the aforementioned issues. The hierarchical representation of clothing utilizes Fourier spherical mapping to define the geometric information of garments within a standard pose space, mapping it onto several 2D frequency domain subspaces. The motion of clothing in tandem with the human body is realized through a hybrid forward dynamic solution, where the internal virtual mechanic’s parameters driving the clothing are learned from text features. A series of qualitative and quantitative experiments reveal that T2C can generate dynamic clothing with a sense of layering, realistic details, and rich textures. The code will be publicly available at https://zhipengyu28.github.io/t2c/ .

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Publication Details

Journal
ACM Transactions on Multimedia Computing Communications and Applications
Published
2025-05-14
DOI
https://doi.org/10.1145/3735642
Citations
1
Primary Topic
3D Shape Modeling and Analysis
Type
article
Field-Weighted Citation Impact
1.33

Funders

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article

T2C: Text-guided 4D Cloth Generation

Binghui Zuo, Zimeng Zhao, Yangang Wang, Zhipeng Yu et al.
1 citations
ACM Transactions on Multimedia Computing Communications and Applications
3D Shape Modeling and Analysis
1.33
article

T2C: Text-guided 4D Cloth Generation

Binghui Zuo, Zimeng Zhao, Yangang Wang, Zhipeng Yu, Y. F. Du, Y. Zheng
article en
1 citations

Abstract

In the age of AIGC, the creation process is increasingly automated. Generating vivid characters with clothing and motions according to scripts or novels is no exception. Unfortunately, the diversity of fabric topologies, the complexity of fabric layering, and the flexibility of fabric motion make most approaches only applicable to motion generation for characters in undressing or tight-fitting clothing. This article introduces a novel approach named T2C , which employs a multi-layered clothing representation and a physics-based clothing animation paradigm to generate text-controlled Clothed 4D Humans, expanding the boundaries of the aforementioned issues. The hierarchical representation of clothing utilizes Fourier spherical mapping to define the geometric information of garments within a standard pose space, mapping it onto several 2D frequency domain subspaces. The motion of clothing in tandem with the human body is realized through a hybrid forward dynamic solution, where the internal virtual mechanic’s parameters driving the clothing are learned from text features. A series of qualitative and quantitative experiments reveal that T2C can generate dynamic clothing with a sense of layering, realistic details, and rich textures. The code will be publicly available at https://zhipengyu28.github.io/t2c/ .

ACM Transactions on Multimedia Computing Communications and ApplicationsVol. 21(7)
Southeast University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province
Openalex Percentile: Top 23%
3D Shape Modeling and Analysis
1.33
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T2C: Text-guided 4D Cloth Generation — Binghui Zuo, Zimeng Zhao, et al. · ACM Transactions on Multimedia Computing Communications and Applications (2025) | TGRS Research Map | TGRS