arXiv:2609.21347v1 Announce Type: new
Abstract: Recent progress in 3D Gaussian Splatting (3DGS) has enabled dense visual SLAM with pinhole cameras, yet most pipelines are not designed for panoramic i...
By Xiangfei Guo, Hao Shi, Yufan Zhang, Zhonghua Yi, Yongqi Mao, Xiaoting Yin, Kaiwei Wang
arXiv:2603.09632v5 Announce Type: replace-cross
Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, subsequently extending into numerous spatial AI ap...
By Yueen Ma, Zenglin Xu, Irwin King
Existing Gaussian-splatting-based monocular Simultaneous Localization and Mapping (SLAM) systems are either tailored to short sequences, are not real-time, or suffer from prohibitive GPU memory requirements, limiting their applicability in realistic, long-horizon scenarios. To address this, we present GLAM-SLAM, a real-time, decoupled Gaussian-splatting SLAM system designed for large-scale outdoor scenes.
arXiv:2608. 15024v1 Announce Type: cross Abstract: Current Vision-based SLAM systems fail catastrophically when motion blur corrupts the visual input, as they attempt the ill-posed inverse problem of recovering sharp content from degraded observations.
By Zhiqiang Hu, Shouren Huang, Masatoshi Ishikawa
VGGT-GS SLAM is a monocular 3D Gaussian Splatting SLAM system that operates on uncalibrated videos. It uses feed‑forward VGGT pose and depth priors to perform submap differentiable bundle adjustment, jointly refining camera poses, a 3D Gaussian map, and submap‑shared intrinsics and distortion parameters via analytic calibration Jacobians. The method introduces Gaussian‑native alignment for camera‑anchored scale refinement between submaps and loop‑closure verification, achieving improved localization accuracy and rendering quality on standard indoor benchmarks.
By Yuhang Han, Hao Wang, Jiaxi Cao, Xingyu Liu
arXiv:2608.31023v1 Announce Type: new
Abstract: We study dynamic Gaussian Splatting from monocular videos. While recent advancements in dynamic Gaussian splatting offer a promising foundation for mod...
By Haozheng Yu, Xinyu Yang, Rundong Luo, Jennifer J. Sun, Bharath Hariharan