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Research PaperResearchia:202602.03147[Artificial Intelligence > AI]

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

Erzhen Hu

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.


Source: arXiv:2602.03838v1 - http://arxiv.org/abs/2602.03838v1 PDF: https://arxiv.org/pdf/2602.03838v1 Original Article: View on arXiv

Submission:2/3/2026
Comments:0 comments
Subjects:AI; Artificial Intelligence
Original Source:
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arXiv: This paper is hosted on arXiv, an open-access repository
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