6 papers
CubifyGS: Object-Centric 3D Gaussian Splatting for Lifelong Dynamic Scene Maintenance
Bohan Ren, Dianyi Yang, Shiyang Liu +5
Lifelong scene mapping under rigid object rearrangement remains a fundamental challenge in robotics. While 3D Gaussian Splatting (3DGS) enables high-fidelity modeling, primitive-le…
CM-EVS: Sparse Panoramic RGB-D-Pose Data for Complete Scene Coverage
Jiale Liu, Jungang Li, Jieming Yu +13
Modern 3D visual learning relies on observations sampled from metric 3D assets, yet existing scans, meshes, point clouds, simulations, and reconstructions do not directly provide a…
Physically Plausible Human-Object Rendering from Sparse Views via 3D Gaussian Splatting
Weiquan Wang, Jun Xiao, Yi Yang +2
Rendering realistic human-object interactions (HOIs) from sparse-view inputs is a challenging yet crucial task for various real-world applications. Existing methods often struggle…
Rendering Multi-Human and Multi-Object with 3D Gaussian Splatting
Weiquan Wang, Jun Xiao, Feifei Shao +3
Reconstructing dynamic scenes with multiple interacting humans and objects from sparse-view inputs is a critical yet challenging task, essential for creating high-fidelity digital…
OpenGS-Fusion: Open-Vocabulary Dense Mapping with Hybrid 3D Gaussian Splatting for Refined Object-Level Understanding
Dianyi Yang, Xihan Wang, Yu Gao +4
Recent advancements in 3D scene understanding have made significant strides in enabling interaction with scenes using open-vocabulary queries, particularly for VR/AR and robotic ap…
Automated 3D-GS Registration and Fusion via Skeleton Alignment and Gaussian-Adaptive Features
Shiyang Liu, Dianyi Yang, Yu Gao +3
In recent years, 3D Gaussian Splatting (3D-GS)-based scene representation demonstrates significant potential in real-time rendering and training efficiency. However, most existing…