Prompt2Poster: Automatically Artistic Chinese Poster Creation from Prompt Only

As a critical component in graphic design, artistic posters are widely applied in the advertising and entertainment industry, thus the automatic poster creation from user-provided prompts has become increasingly desired recently. Although existing Text2Image methods create impressive images aligned with given prompts, they fail to generate ideal artistic posters, especially with Chinese texts. To create desired artistic Chinese posters including an aligned background, reasonable layouts, and stylized graphical texts from given prompts only, we propose an automatic poster creation framework, named Prompt2Poster. Our framework utilizes the capacity of the powerful Large Language Model (LLM) to extract user intention from provided prompts and generate the aligned background. Although only taking a user prompt as the input, linguistic, visual, and geometrical information is fully utilized in the framework, bringing the ability to fit different distributions. To achieve the use of multi-modal information in the framework, two carefully designed modules, Controllable Layout Generator (CLG) and Graphical Text Generator (GTG) are proposed, leading to accurate and pleasurable visual results. Comprehensive experiments demonstrate that our Prompt2Poster achieves superior performance, especially in text quality and visual harmony.

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Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1145/3664647.3681495
Citations
3
Primary Topic
Multimodal Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.75
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article

Prompt2Poster: Automatically Artistic Chinese Poster Creation from Prompt Only

Liuhan Chen, Yunyang Ge, Xinhua Cheng, Shaodong Wang et al.
3 citations
Multimodal Machine Learning Applications
0.75
article

Prompt2Poster: Automatically Artistic Chinese Poster Creation from Prompt Only

Liuhan Chen, Yunyang Ge, Xinhua Cheng, Shaodong Wang, Qian Wang, Haiyang Zhou
article en
3 citations

Abstract

As a critical component in graphic design, artistic posters are widely applied in the advertising and entertainment industry, thus the automatic poster creation from user-provided prompts has become increasingly desired recently. Although existing Text2Image methods create impressive images aligned with given prompts, they fail to generate ideal artistic posters, especially with Chinese texts. To create desired artistic Chinese posters including an aligned background, reasonable layouts, and stylized graphical texts from given prompts only, we propose an automatic poster creation framework, named Prompt2Poster. Our framework utilizes the capacity of the powerful Large Language Model (LLM) to extract user intention from provided prompts and generate the aligned background. Although only taking a user prompt as the input, linguistic, visual, and geometrical information is fully utilized in the framework, bringing the ability to fit different distributions. To achieve the use of multi-modal information in the framework, two carefully designed modules, Controllable Layout Generator (CLG) and Graphical Text Generator (GTG) are proposed, leading to accurate and pleasurable visual results. Comprehensive experiments demonstrate that our Prompt2Poster achieves superior performance, especially in text quality and visual harmony.

Peking University (CN), Peng Cheng Laboratory (CN)
Openalex Percentile: Top 27%
Multimodal Machine Learning Applications
0.75
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Prompt2Poster: Automatically Artistic Chinese Poster Creation from Prompt Only — Liuhan Chen, Yunyang Ge, et al. · (2024) | TGRS Research Map | TGRS