CamLit: Unified Video Diffusion with Explicit Camera and Lighting Control

TL;DR

CamLit introduces a unified video diffusion model capable of synthesizing temporally coherent videos with novel viewpoints and relighting from a single image, enabling high-quality control over camera and lighting conditions.

Contribution

This work is the first to unify view synthesis and relighting in a single diffusion model for videos, providing integrated control and high-quality outputs.

Findings

Achieves high-fidelity novel view synthesis and relighting

Produces temporally coherent and spatially aligned videos

Maintains competitive performance with state-of-the-art methods

Abstract

We present CamLit, the first unified video diffusion model that jointly performs novel view synthesis (NVS) and relighting from a single input image. Given one reference image, a user-defined camera trajectory, and an environment map, CamLit synthesizes a video of the scene from new viewpoints under the specified illumination. Within a single generative process, our model produces temporally coherent and spatially aligned outputs, including relit novel-view frames and corresponding albedo frames, enabling high-quality control of both camera pose and lighting. Qualitative and quantitative experiments demonstrate that CamLit achieves high-fidelity outputs on par with state-of-the-art methods in both novel view synthesis and relighting, without sacrificing visual quality in either task. We show that a single generative model can effectively integrate camera and lighting control, simplifying the video generation pipeline while maintaining competitive performance and consistent realism.