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.
@article{arxiv.2602.03838,
title = {PrevizWhiz: Combining Rough 3D Scenes and 2D Video to Guide Generative Video Previsualization},
author = {Erzhen Hu and Frederik Brudy and David Ledo and George Fitzmaurice and Fraser Anderson},
journal= {arXiv preprint arXiv:2602.03838},
year = {2026}
}
Comments
21 pages, 13 figures; accepted and to appear at CHI 2026