PhysAnimator: Physics-Guided Generative Cartoon Animation

• URL: http://arxiv.org/abs/2501.16550v1
• Date: Mon, 27 Jan 2025 22:48:36 GMT
• Title: PhysAnimator: Physics-Guided Generative Cartoon Animation
• Authors: Tianyi Xie, Yiwei Zhao, Ying Jiang, Chenfanfu Jiang,
• Abstract summary: We introduce PhysAnimator, a novel approach for generating anime-stylized animation from static anime illustrations. To capture the fluidity and exaggeration characteristic of anime, we perform image-space deformable body simulations on extracted mesh geometries. We extract and warp sketches from the simulation sequence, generating a texture-agnostic representation, and employ a sketch-guided video diffusion model to synthesize high-quality animation frames.
• Score: 19.124321553546242
• License:
• Abstract: Creating hand-drawn animation sequences is labor-intensive and demands professional expertise. We introduce PhysAnimator, a novel approach for generating physically plausible meanwhile anime-stylized animation from static anime illustrations. Our method seamlessly integrates physics-based simulations with data-driven generative models to produce dynamic and visually compelling animations. To capture the fluidity and exaggeration characteristic of anime, we perform image-space deformable body simulations on extracted mesh geometries. We enhance artistic control by introducing customizable energy strokes and incorporating rigging point support, enabling the creation of tailored animation effects such as wind interactions. Finally, we extract and warp sketches from the simulation sequence, generating a texture-agnostic representation, and employ a sketch-guided video diffusion model to synthesize high-quality animation frames. The resulting animations exhibit temporal consistency and visual plausibility, demonstrating the effectiveness of our method in creating dynamic anime-style animations.

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