Mono4DGS-HDR: High Dynamic Range 4D Gaussian Splatting from
  Alternating-exposure Monocular Videos
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.
68f86c7b7669bcaeecce0e4e
Jinfeng Liu
claimed_verified
2025-10-22T15:42:44.786Z
669dc7a932408ac579928f1e
/avatars/4e9d248749ea554e7803ac5f693ad00f.svg
Jinfeng Liu
user
jinfengliu26
68f86c7b7669bcaeecce0e4f
Lingtong Kong
68f86c7b7669bcaeecce0e50
Mi Zhou
68f86c7b7669bcaeecce0e51
Jinwen Chen
68f86c7b7669bcaeecce0e52
Dan Xu
claimed_verified
2025-10-22T15:42:42.192Z
66feab48651e00e22f33222e
/avatars/7344377e2c796c7ec85194bb2fc78521.svg
Dan Xu
user
danxuhk
Mono4DGS-HDR: High Dynamic Range 4D Gaussian Splatting from
  Alternating-exposure Monocular Videos
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.
A system for reconstructing 4D HDR scenes from unposed LDR videos using Gaussian Splatting with two-stage optimization and temporal luminance regularization.
Gaussian Splatting orthographic camera coordinate space world space temporal luminance regularization HDR video reconstruction