3DGS Storyboard Automation: An Automated Pipeline from 2D Storyboards to Navigable 3D Gaussian Scenes

This article introduces an innovative automated machine learning pipeline—3DGS Storyboard Automation. By combining large world models with 3D Gaussian splatting technology, it converts 2D film storyboards into navigable 3D Gaussian environments, opening up new possibilities for film previsualization, virtual production, and interactive storytelling.

Traditional storyboards are 2D static images that struggle to fully convey spatial relationships, camera movements, and scene atmosphere. With the rise of virtual production, the industry urgently needs tools that can provide 3D space previews in the early stages. 3DGS Storyboard Automation is an innovative attempt to address this need, bridging the gap from concept art to 3D realization.

3D Gaussian Splatting Technology

3D Gaussian Splatting (3DGS) represents scenes using millions of 3D Gaussian distributions, each with position, covariance, color, and transparency. It achieves real-time rendering through rasterization, with advantages including fast rendering and high-quality new view synthesis, making it suitable for dynamic scene editing.

Role of Large World Models

Large world models understand 3D spatial structures and physical laws by learning massive visual data. They infer the complete 3D scene geometry and appearance from 2D storyboards, including semantic understanding (object categories, occlusion relationships, lighting, etc.), and generate coherent 3D environments using prior knowledge.

The automated workflow consists of four key stages:

1. Storyboard Parsing: Analyze 2D storyboard images to extract composition, camera parameters, and scene elements;
2. 3D Reconstruction: Large world models generate initial 3D representations, solving the ill-posed problem of recovering 3D from images;
3. 3D Gaussian Generation: Convert reconstruction results into Gaussian splatting representations and optimize millions of Gaussian parameters;
4. Scene Optimization and Export: After optimization, export to real-time rendering engines or virtual production platforms.

This technology has a wide range of application scenarios:

• Film Pre-Production: Directors can experience camera scheduling in a virtual environment and identify spatial issues;
• Game Development: Concept art is directly converted into explorable 3D prototypes, shortening the cycle;
• Architectural Visualization: Hand-drawn sketches quickly generate navigable virtual spaces;
• Virtual Production Stages: Lower the threshold for preparing 3D assets for LED wall backgrounds.

Current Challenges

• The detail richness and geometric accuracy of automatically generated scenes still need improvement;
• Limited ability to handle complex dynamic scenes.

Future Directions

• Integrate with generative AI to support scene modification via natural language;
• Add real-time collaboration features for multi-person online review and adjustment;
• Integrate more industry-standard toolchains to form a seamless workflow.

3DGS Storyboard Automation represents the democratization of creative tools. It lowers the threshold for 3D scene generation, allowing more creative talents to turn visual imaginations into experiential realities. The tool becomes a creative amplifier, promoting the liberation of creative expression in the new era of AI-assisted creation.