Light-X: Generative 4D Video Rendering with Camera and Illumination Control

TL;DR

Light-X is a novel framework for controllable 4D video rendering that jointly manages camera and illumination, enabling high-quality, dynamic scene synthesis from monocular videos with disentangled geometry and lighting cues.

Contribution

The paper introduces Light-X, a new generative model that combines explicit geometry and lighting disentanglement with a novel training pipeline, advancing controllable 4D video synthesis.

Findings

Outperforms baseline methods in joint camera and illumination control

Achieves superior relighting quality under various conditions

Successfully synthesizes diverse dynamic scenes from monocular footage

Abstract

Recent advances in illumination control extend image-based methods to video, yet still facing a trade-off between lighting fidelity and temporal consistency. Moving beyond relighting, a key step toward generative modeling of real-world scenes is the joint control of camera trajectory and illumination, since visual dynamics are inherently shaped by both geometry and lighting. To this end, we present Light-X, a video generation framework that enables controllable rendering from monocular videos with both viewpoint and illumination control. 1) We propose a disentangled design that decouples geometry and lighting signals: geometry and motion are captured via dynamic point clouds projected along user-defined camera trajectories, while illumination cues are provided by a relit frame consistently projected into the same geometry. These explicit, fine-grained cues enable effective disentanglement and guide high-quality illumination. 2) To address the lack of paired multi-view and multi-illumination videos, we introduce Light-Syn, a degradation-based pipeline with inverse-mapping that synthesizes training pairs from in-the-wild monocular footage. This strategy yields a dataset covering static, dynamic, and AI-generated scenes, ensuring robust training. Extensive experiments show that Light-X outperforms baseline methods in joint camera-illumination control and surpasses prior video relighting methods under both text- and background-conditioned settings.