PrevizWhiz: Combining Rough 3D Scenes and 2D Video to Guide Generative Video Previsualization
This addresses the need for more accessible and expressive previsualization tools for filmmakers and 3D animation experts, though it is incremental in improving existing workflows.
The paper tackles the problem of inefficient and technically demanding previsualization in filmmaking by introducing PrevizWhiz, a system that combines rough 3D scenes with generative models to create stylized video previews, resulting in lowered technical barriers and accelerated creative iteration as demonstrated in a study with filmmakers.
In pre-production, filmmakers and 3D animation experts must rapidly prototype ideas to explore a film's possibilities before fullscale production, yet conventional approaches involve trade-offs in efficiency and expressiveness. Hand-drawn storyboards often lack spatial precision needed for complex cinematography, while 3D previsualization demands expertise and high-quality rigged assets. To address this gap, we present PrevizWhiz, a system that leverages rough 3D scenes in combination with generative image and video models to create stylized video previews. The workflow integrates frame-level image restyling with adjustable resemblance, time-based editing through motion paths or external video inputs, and refinement into high-fidelity video clips. A study with filmmakers demonstrates that our system lowers technical barriers for film-makers, accelerates creative iteration, and effectively bridges the communication gap, while also surfacing challenges of continuity, authorship, and ethical consideration in AI-assisted filmmaking.