Mono4DGS-HDR：基于交替曝光单目视频的高动态范围4D高斯溅射重建

Mono4DGS-HDR: High Dynamic Range 4D Gaussian Splatting from Alternating-exposure Monocular Videos

October 21, 2025

作者: Jinfeng Liu, Lingtong Kong, Mi Zhou, Jinwen Chen, Dan Xu

cs.AI

摘要

我们推出了Mono4DGS-HDR，这是首个从交替曝光拍摄的无位姿单目低动态范围（LDR）视频中重建可渲染四维高动态范围（HDR）场景的系统。为应对这一极具挑战性的问题，我们提出了一个基于高斯溅射的两阶段优化统一框架。第一阶段在正交相机坐标系中学习视频HDR的高斯表示，无需相机位姿即可实现稳健的初始HDR视频重建。第二阶段将视频高斯转换至世界坐标系，并与相机位姿联合优化世界高斯。此外，我们提出了一种时间亮度正则化策略，以增强HDR外观的时间一致性。鉴于该任务此前未被研究，我们利用公开数据集构建了一个新的HDR视频重建评估基准。大量实验表明，Mono4DGS-HDR在渲染质量和速度上均显著优于从现有最先进方法改编的替代方案。

English

We introduce Mono4DGS-HDR, the first system for reconstructing renderable 4D high dynamic range (HDR) scenes from unposed monocular low dynamic range (LDR) videos captured with alternating exposures. To tackle such a challenging problem, we present a unified framework with two-stage optimization approach based on Gaussian Splatting. The first stage learns a video HDR Gaussian representation in orthographic camera coordinate space, eliminating the need for camera poses and enabling robust initial HDR video reconstruction. The second stage transforms video Gaussians into world space and jointly refines the world Gaussians with camera poses. Furthermore, we propose a temporal luminance regularization strategy to enhance the temporal consistency of the HDR appearance. Since our task has not been studied before, we construct a new evaluation benchmark using publicly available datasets for HDR video reconstruction. Extensive experiments demonstrate that Mono4DGS-HDR significantly outperforms alternative solutions adapted from state-of-the-art methods in both rendering quality and speed.