High-Fidelity SLAM Using Gaussian Splatting with Rendering-Guided Densification and Regularized Optimization

arXiv:2403.12535v1 Announce Type: cross
Abstract: We propose a dense RGBD SLAM system based on 3D Gaussian Splatting that provides metrically accurate pose tracking and visually realistic reconstruction. To this end, we first propose a Gaussian densification strategy based on the rendering loss to map unobserved areas and refine reobserved areas. Second, we introduce extra regularization parameters to alleviate the forgetting problem in the continuous mapping problem, where parameters tend to overfit the latest frame and result in decreasing rendering quality …

abstract arxiv cs.cv cs.ro fidelity loss map optimization refine rendering slam strategy tracking type