PrevizWhiz: Combining Rough 3D Scenes and 2D Video to Guide Generative Video Previsualization

TL;DR

PrevizWhiz is a system that combines rough 3D scenes with generative models to create stylized, editable video previews, streamlining previsualization for filmmakers and reducing technical barriers.

Contribution

It introduces an integrated workflow that combines 3D scene roughs with generative models for stylized video previsualization, enhancing efficiency and expressiveness in filmmaking.

Findings

Reduces previsualization time for filmmakers

Improves communication between creators and stakeholders

Highlights ethical considerations in AI-assisted filmmaking

Abstract

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.