SandSim: Curve-Guided Gaussian Splatting for Reconstructing Sand Painting Processes

TL;DR

SandSim is a novel framework that reconstructs realistic sand painting processes from a single image by modeling strokes with a curve-guided Gaussian representation and scene-aware planning.

Contribution

It introduces a curve-guided Gaussian stroke model, a subtractive compositing scheme, and a semantic-guided planning module for coherent sand painting reconstruction.

Findings

Produces temporally coherent and realistic sand painting sequences.

Achieves improved reconstruction quality over existing methods.

Enables integration with physics-based sand simulators for editing.

Abstract

Sand painting is a process-driven art where visual appearance emerges from granular accumulation. Given a single image, reconstructing a plausible sand painting process requires modeling coherent stroke structures and material-dependent effects. Existing methods, including stroke-based optimization and diffusion-based video synthesis, often lack structural coherence and material consistency, leading to unrealistic drawing sequences. We present SandSim, a framework that reconstructs a sand painting process from a single image. We introduce a curve-guided Gaussian representation that models strokes as sequences of anisotropic primitives along continuous trajectories, whose smooth kernels capture the soft boundaries of sand strokes and enable coherent stroke formation. We further adopt a subtractive compositing scheme to model light attenuation during sand accumulation. We incorporate a semantic-guided planning module for scene decomposition and drawing order inference. Our framework jointly optimizes stroke geometry and appearance and can be integrated with a physics-based simulator for interactive sand dynamics and editing. Experiments show that our method produces temporally coherent and visually realistic results, achieving improved reconstruction quality and perceptual fidelity compared to existing approaches.