PhysAnimator: Physics-Guided Generative Cartoon Animation

2025-01-27

AI Summary

To address the challenge of balancing physical plausibility with stylized aesthetics in cartoon animation—while reducing reliance on expert skill—this paper proposes an end-to-end framework integrating physics-based simulation and generative modeling. Methodologically, it introduces the first image-space deformable-body physics simulator coupled with an energy-based stroke interaction mechanism, unifying exaggerated motion and realistic physical constraints. It further proposes a texture-agnostic sketch representation and a sketch-guided video diffusion synthesis framework. Key technical components include image-grid deformation simulation, energy-driven dynamical modeling, skeletal anchor binding, and deformation mapping. Experiments demonstrate that our approach significantly outperforms purely data-driven methods in scenarios such as wind-responsive dynamics and limb-exaggerated motion, yielding animations with high temporal coherence and visual plausibility, while enabling real-time artistic user intervention.

Technology Category

• Computer Vision: Low Level & Physics-based Vision
• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Web Mining and Content Analysis: Web data generation and simulation
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

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.

Problem

• Physically-based Animation
• Cartoon Rendering
• Efficient Production

Innovation

• PhysAnimator
• Physics-based Animation
• Data-driven Animation