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Generating Animated Layouts as Structured Text Representations

2 May 2025
Yeonsang Shin
Jihwan Kim
Yumin Song
Kyungseung Lee
Hyunhee Chung
Taeyoung Na
    DiffM
    VGen
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Abstract

Despite the remarkable progress in text-to-video models, achieving precise control over text elements and animated graphics remains a significant challenge, especially in applications such as video advertisements. To address this limitation, we introduce Animated Layout Generation, a novel approach to extend static graphic layouts with temporal dynamics. We propose a Structured Text Representation for fine-grained video control through hierarchical visual elements. To demonstrate the effectiveness of our approach, we present VAKER (Video Ad maKER), a text-to-video advertisement generation pipeline that combines a three-stage generation process with Unstructured Text Reasoning for seamless integration with LLMs. VAKER fully automates video advertisement generation by incorporating dynamic layout trajectories for objects and graphics across specific video frames. Through extensive evaluations, we demonstrate that VAKER significantly outperforms existing methods in generating video advertisements. Project Page:this https URL

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@article{shin2025_2505.00975,
  title={ Generating Animated Layouts as Structured Text Representations },
  author={ Yeonsang Shin and Jihwan Kim and Yumin Song and Kyungseung Lee and Hyunhee Chung and Taeyoung Na },
  journal={arXiv preprint arXiv:2505.00975},
  year={ 2025 }
}
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