5 papers
CL-Splats: Continual Learning of Gaussian Splatting with Local Optimization
Jan Ackermann, Jonas Kulhanek, Shengqu Cai +5
In dynamic 3D environments, accurately updating scene representations over time is crucial for applications in robotics, mixed reality, and embodied AI. As scenes evolve, efficient…
LODGE: Level-of-Detail Large-Scale Gaussian Splatting with Efficient Rendering
Jonas Kulhanek, Marie-Julie Rakotosaona, Fabian Manhardt +5
In this work, we present a novel level-of-detail (LOD) method for 3D Gaussian Splatting that enables real-time rendering of large-scale scenes on memory-constrained devices. Our ap…
WildGS-SLAM: Monocular Gaussian Splatting SLAM in Dynamic Environments
Jianhao Zheng, Zihan Zhu, Valentin Bieri +3
We present WildGS-SLAM, a robust and efficient monocular RGB SLAM system designed to handle dynamic environments by leveraging uncertainty-aware geometric mapping. Unlike tradition…
No Pose, No Problem: Surprisingly Simple 3D Gaussian Splats from Sparse Unposed Images
Botao Ye, Sifei Liu, Haofei Xu +4
We introduce NoPoSplat, a feed-forward model capable of reconstructing 3D scenes parameterized by 3D Gaussians from \textit{unposed} sparse multi-view images. Our model, trained ex…
DepthSplat: Connecting Gaussian Splatting and Depth
Haofei Xu, Songyou Peng, Fangjinhua Wang +4
Gaussian splatting and single-view depth estimation are typically studied in isolation. In this paper, we present DepthSplat to connect Gaussian splatting and depth estimation and…