4 citations · 8 across the 15 of their papers we have counts for
5 papers · 1 filter
3D Gaussian Splatting in Robotics: A Survey
Siting Zhu, Guangming Wang, Xin Kong +2
Dense 3D representations of the environment have been a long-term goal in the robotics field. While previous Neural Radiance Fields (NeRF) representation have been prevalent for it…
Towards Autonomous Indoor Parking: A Globally Consistent Semantic SLAM System and A Semantic Localization Subsystem
Yichen Sha, Siting Zhu, Hekui Guo +2
We propose a globally consistent semantic SLAM system (GCSLAM) and a semantic-fusion localization subsystem (SF-Loc), which achieves accurate semantic mapping and robust localizati…
NeuroGauss4D-PCI: 4D Neural Fields and Gaussian Deformation Fields for Point Cloud Interpolation
Chaokang Jiang, Dalong Du, Jiuming Liu +5
Point Cloud Interpolation confronts challenges from point sparsity, complex spatiotemporal dynamics, and the difficulty of deriving complete 3D point clouds from sparse temporal in…
DVLO: Deep Visual-LiDAR Odometry with Local-to-Global Feature Fusion and Bi-Directional Structure Alignment
Jiuming Liu, Dong Zhuo, Zhiheng Feng +4
Information inside visual and LiDAR data is well complementary derived from the fine-grained texture of images and massive geometric information in point clouds. However, it remain…
SemGauss-SLAM: Dense Semantic Gaussian Splatting SLAM
Siting Zhu, Renjie Qin, Guangming Wang +2
We propose SemGauss-SLAM, a dense semantic SLAM system utilizing 3D Gaussian representation, that enables accurate 3D semantic mapping, robust camera tracking, and high-quality ren…