DragPhysSVG: Bridging Vector Graphics and Particle Dynamics for User-Controlled Animation

Scalable vector graphics (SVGs) represent visual content as editable vector paths, but their path structure reflects how an image is drawn rather than how the depicted object is physically organized. This mismatch makes physically grounded animation of unrigged SVGs challenging: parts belonging to the same body should move coherently, articulated parts should remain connected, and embedded details should follow their supporting bodies. Existing SVG animation methods often rely on predefined structure or direct path deformation, while particle-based physical models do not preserve the path organization required for editable vector output. We introduce DragPhysSVG, a structured particle representation that bridges vector graphics and particle-based dynamics. Specifically, SVG paths are sampled into particles with particle-to-path correspondence, while a vision-language model infers their latent physical organization, including body groupings, embedded details, and articulated connections. These relations form a structured graph augmenting the particle representation with the original SVG organization. Given a user drag, a pretrained physical diffusion model predicts particle motion, and our articulated-flow guidance preserves attachments and constrains relative motion across connected parts. Resulting trajectories are transferred back to the original paths through path-local deformation, producing editable animated SVGs. Experiments on articulated SVGs demonstrate improved structural coherence, joint stability, and drag controllability while preserving vector organization. Video animations are available on https://dragphyssvg.github.io/dragphyssvg/