Cinematic Gaussians: Real-Time HDR Radiance Fields with Depth of Field

Abstract
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.
Description

CCS Concepts: Computing methodologies → Computational photography; Image-based rendering

        
@article{
10.1111:cgf.15214
, journal = {Computer Graphics Forum}, title = {{
Cinematic Gaussians: Real-Time HDR Radiance Fields with Depth of Field
}}, author = {
Wang, Chao
and
Wolski, Krzysztof
and
Kerbl, Bernhard
and
Serrano, Ana
and
Bemama, Mojtaba
and
Seidel, Hans-Peter
and
Myszkowski, Karol
and
Leimkühler, Thomas
}, year = {
2024
}, publisher = {
The Eurographics Association and John Wiley & Sons Ltd.
}, ISSN = {
1467-8659
}, DOI = {
10.1111/cgf.15214
} }
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