MG-Gen: Single Image to Motion Graphics Generation
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866913939551420416 |
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| author | Shirakawa, Takahiro Suzuki, Tomoyuki Narumoto, Takuto Haraguchi, Daichi |
| author_facet | Shirakawa, Takahiro Suzuki, Tomoyuki Narumoto, Takuto Haraguchi, Daichi |
| contents | We introduce MG-Gen, a framework that generates motion graphics directly from a single raster image. MG-Gen decompose a single raster image into layered structures represented as HTML, generate animation scripts for each layer, and then render them into a video. Experiments confirm MG-Gen generates dynamic motion graphics while preserving text readability and fidelity to the input conditions, whereas state-of-the-art image-to-video generation methods struggle with them. The code is available at https://github.com/CyberAgentAILab/MG-GEN. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_02361 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MG-Gen: Single Image to Motion Graphics Generation Shirakawa, Takahiro Suzuki, Tomoyuki Narumoto, Takuto Haraguchi, Daichi Graphics Computer Vision and Pattern Recognition We introduce MG-Gen, a framework that generates motion graphics directly from a single raster image. MG-Gen decompose a single raster image into layered structures represented as HTML, generate animation scripts for each layer, and then render them into a video. Experiments confirm MG-Gen generates dynamic motion graphics while preserving text readability and fidelity to the input conditions, whereas state-of-the-art image-to-video generation methods struggle with them. The code is available at https://github.com/CyberAgentAILab/MG-GEN. |
| title | MG-Gen: Single Image to Motion Graphics Generation |
| topic | Graphics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2504.02361 |