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.

翻译：辐射场方法代表了从多视角照片重建复杂场景的最先进技术。然而，这些重建通常存在以下一个或两个限制：首先，它们通常以低动态范围表示场景，这限制了其在均匀光照环境下的使用，并阻碍了沉浸式观看体验。其次，它们依赖于针孔相机模型，假设输入图像中的所有场景元素均处于焦点状态，这带来了实际挑战，并在新视角合成过程中使重新对焦变得复杂。针对这些限制，我们提出了一种基于3D高斯泼溅的轻量级方法，该方法利用场景在不同曝光时间、光圈和对焦距离下拍摄的多视角低动态范围图像作为输入，以重建高动态范围辐射场。通过结合基于薄透镜相机模型的高斯解析卷积以及色调映射模块，我们的重建能够渲染具有灵活重新对焦能力的高动态范围内容。我们证明，我们对高动态范围和景深的联合处理实现了实时电影级渲染，其性能优于现有最先进技术。