5 papers
F SLAM: Turning Feed-Forward Geometry into Persistent Factors for SLAM
Zhisong Xu, Fan Zhu, Jiawei Qian +3
Feed-forward 3D models provide strong multi-view geometric priors, while on- line simultaneous localization and mapping (SLAM) relies mainly on local mea- surements and can accumul…
MyGO-Splat: Multi-Objective Closed-Loop Geometric Feedback for RGB-Only Gaussian SLAM
Fan Zhu, Ziyu Chen, Zhenjun Zhao +5
Real-time monocular Simultaneous Localization and Mapping (SLAM) fundamentally suffers from scale ambiguity and a lack of geometric self-correction. While 3D Gaussian Splatting (3D…
MMD-SLAM: Structure-Enhanced Multi-Meta Gaussian Distribution-Guided Visual SLAM
Fan Zhu, Ziyu Chen, Peichen Liu +6
3D Gaussian Splatting (3DGS) has significantly boosted novel view synthesis and high-fidelity scene reconstruction, expanding the potential of 3DGS-based Visual Simultaneous Locali…
LR-SGS: Robust LiDAR-Reflectance-Guided Salient Gaussian Splatting for Self-Driving Scene Reconstruction
ZY Chen, F Zhu, H Zhu +4
Recent 3D Gaussian Splatting (3DGS) methods have demonstrated the feasibility of self-driving scene reconstruction and novel view synthesis. However, most existing methods either r…
FGO-SLAM: Enhancing Gaussian SLAM with Globally Consistent Opacity Radiance Field
Fan Zhu, Yifan Zhao, Ziyu Chen +2
Visual SLAM has regained attention due to its ability to provide perceptual capabilities and simulation test data for Embodied AI. However, traditional SLAM methods struggle to mee…