Cinematic Compositing Using Character-Environment-Harmonized Video Generation Models

TL;DR

Given green-screen character footage, predicted depth, and a text prompt, our method synthesizes cinematic environments while preserving physical interaction and harmonizing lighting between characters, props, and the scene. The unified framework supports relighting, prop replacement, and prop/background generation through adaptive RGB, depth, and unconditioned input regions.

RGB
Depth
Input Conditions Visualization
Result

Bright kitchen with warm morning light and green styling.

Input Conditions Visualization
Result

Outdoor tree shade with moving highlights and leafy shadows.

Input Conditions Visualization
Result

Futuristic lab with blue neon profile highlights.

RGB
Depth
Input Conditions Visualization
Result

Gothic church with candles, green clothing, and an ancient book.

Input Conditions Visualization
Result

Gothic church variation with burgundy velvet and candle illumination.

Input Conditions Visualization
Result

Modern library with bright natural light and navy styling.

Abstract

Cinematic compositing aims to integrate green-screen characters into novel environments while maintaining physical and photometric realism. Previous methods often fail to capture the complex bidirectional interactions between characters and their surroundings, which we characterize as Character-to-Environment (C2E) physical interaction and Environment-to-Character (E2C) lighting harmonization. To address this, we propose an end-to-end video diffusion framework that jointly models C2E and E2C interactions, specifically handling the challenges of interactive props. Our approach introduces a tri-mask-guided architecture with RGB-D joint denoising to ensure physically consistent interactions among the character, props, and environment. We further develop an efficient prior-driven data curation pipeline to construct high-quality relighting pairs without expensive rendering. Finally, a reference-conditioned mechanism enables controllable environment synthesis and precise prop replacement. Extensive experiments demonstrate that our framework significantly outperforms existing methods in cinematic-quality dynamic video compositing.

Results

Green Screen Video
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Green Screen Video
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Green Screen Video
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Green Screen Video
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Green Screen Video
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Green Screen Video
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Green Screen Video
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Green Screen Video
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Application on Real-world Videos

Real-world Video
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Real-world Video
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Real-world Video
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Real-world Video
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Real-world Video
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Real-world Video
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Real-world Video
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Real-world Video
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