Cinematic Gaussians: Real-Time HDR Radiance Fields with Depth of Field
<|reference_start|>Cinematic Gaussians: Real-Time HDR Radiance Fields with Depth of Field: Radiance field methods represent the state of the art in reconstructing complex scenes from multi-view photos. However, these reconstructions often suffer from one or both of the following limitations: First, they typically represent scenes in low dynamic range (LDR), which restricts their use to evenly lit environments and hinders immersive viewing experiences. Secondly, their reliance on a pinhole camera model, assuming all scene elements are in focus in the input images, presents practical challenges and complicates refocusing during novel-view synthesis. Addressing these limitations, we present a lightweight method based on 3D Gaussian Splatting that utilizes multi-view LDR images of a scene with varying exposure times, apertures, and focus distances as input to reconstruct a high-dynamic-range (HDR) radiance field. By incorporating analytical convolutions of Gaussians based on a thin-lens camera model as well as a tonemapping module, our reconstructions enable the rendering of HDR content with flexible refocusing capabilities. We demonstrate that our combined treatment of HDR and depth of field facilitates real-time cinematic rendering, outperforming the state of the art.<|reference_end|>
@article{wang2024cinematic,
    title={Cinematic Gaussians: Real-Time HDR Radiance Fields with Depth of Field},
    author={Chao Wang, Krzysztof Wolski, Bernhard Kerbl, Ana Serrano, Mojtaba
  Bemana, Hans-Peter Seidel, Karol Myszkowski, and Thomas Leimk"uhler},
    journal={arXiv preprint arXiv:2406.07329},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.07329},
    primaryClass={cs.CV eess.IV}
}