Paper ID: 2504.02361 • Published Apr 3, 2025

MG-Gen: Single Image to Motion Graphics Generation with Layer Decomposition

Takahiro Shirakawa, Tomoyuki Suzuki, Daichi Haraguchi
CyberAgent
TL;DR
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General image-to-video generation methods often produce suboptimal animations that do not meet the requirements of animated graphics, as they lack active text motion and exhibit object distortion. Also, code-based animation generation methods typically require layer-structured vector data which are often not readily available for motion graphic generation. To address these challenges, we propose a novel framework named MG-Gen that reconstructs data in vector format from a single raster image to extend the capabilities of code-based methods to enable motion graphics generation from a raster image in the framework of general image-to-video generation. MG-Gen first decomposes the input image into layer-wise elements, reconstructs them as HTML format data and then generates executable JavaScript code for the reconstructed HTML data. We experimentally confirm that \ours{} generates motion graphics while preserving text readability and input consistency. These successful results indicate that combining layer decomposition and animation code generation is an effective strategy for motion graphics generation.

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