Dynamic Gaussians Mesh: Consistent Mesh Reconstruction from Dynamic Scenes
Isabella Liu, Hao Su, Xiaolong Wang

TL;DR
The paper presents DG-Mesh, a novel framework that reconstructs high-quality, time-consistent 3D meshes from dynamic scenes using Gaussian splatting, enabling detailed and temporally coherent mesh reconstructions for graphics applications.
Contribution
Introduces DG-Mesh, a new method leveraging 3D Gaussian splatting and Gaussian-Mesh Anchoring for high-fidelity, time-consistent mesh reconstruction from dynamic observations.
Findings
DG-Mesh outperforms baselines in mesh reconstruction quality.
The method achieves better temporal consistency in dynamic scenes.
DG-Mesh enables applications like texture editing on moving objects.
Abstract
Modern 3D engines and graphics pipelines require mesh as a memory-efficient representation, which allows efficient rendering, geometry processing, texture editing, and many other downstream operations. However, it is still highly difficult to obtain high-quality mesh in terms of detailed structure and time consistency from dynamic observations. To this end, we introduce Dynamic Gaussians Mesh (DG-Mesh), a framework to reconstruct a high-fidelity and time-consistent mesh from dynamic input. Our work leverages the recent advancement in 3D Gaussian Splatting to construct the mesh sequence with temporal consistency from dynamic observations. Building on top of this representation, DG-Mesh recovers high-quality meshes from the Gaussian points and can track the mesh vertices over time, which enables applications such as texture editing on dynamic objects. We introduce the Gaussian-Mesh…
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Taxonomy
TopicsRemote Sensing and LiDAR Applications · Computer Graphics and Visualization Techniques · Advanced Vision and Imaging
MethodsPruning
