Con-DSO introduces a consistency-aware RGB‑D direct sparse odometry framework that learns pixel‑level photometric and geometric uncertainty from adjacent RGB‑D frame pairs. The network predicts uncertainties that are converted into pairwise quality scores, guiding support‑pixel selection and forming a host‑side quality prior for keyframe tracking. Experiments on five public benchmarks show that this approach reduces absolute trajectory error by over 20% on ICL‑NUIM and by 50–80% on other datasets, improving robustness in challenging environments.
By Haolan Zhang, Thanh Nguyen Canh, Chenghao Li, Ziyan Gao, Xiongwen Jiang, Nak Young Chong
arXiv:2609.25746v1 Announce Type: cross
Abstract: ICP-based 3D Gaussian Splatting (3DGS) SLAM tracks in real time by registering incoming frames against map Gaussians, using each primitive's covarian...
By Edward Beng Wai Tan, Siew-Kei Lam
The paper introduces LingGS, an online monocular RGB Gaussian splatting SLAM system that decouples feed‑forward geometry prediction from camera tracking. By leveraging a frozen streaming 3D foundation model as a virtual RGB‑D sensor for depth estimation and an explicit geometric solver for camera motion via feature reprojection, LingGS achieves higher tracking accuracy than learned predictions. Experiments on indoor and outdoor datasets demonstrate significant improvements in reconstruction quality, achieving about 7 FPS on a single RTX 4090 and 2–3× the throughput of prior SLAM systems.
By Da Li, Yihan Zang, Ivan Viola, Zeyu Wang, Dominik Engel
arXiv:2609.15795v2 Announce Type: replace
Abstract: Streaming geometric foundation models are emerging as a compelling alternative to SLAM systems. Yet this streaming nature introduces a fundamental...
By Mingkai Liu, Hao Zhao, Xingxing Zuo
arXiv:2609.15795v1 Announce Type: new
Abstract: Streaming geometric foundation models are emerging as a compelling alternative to SLAM systems. Yet this streaming nature introduces a fundamental issu...
By Mingkai Liu, Hao Zhao, Xingxing Zuo
arXiv:2606. 29237v1 Announce Type: cross Abstract: Robust robot autonomy depends on scene representations that remain stable enough to support localization, navigation, and downstream decision making in dynamic environments.
By Qixin Xiao
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
The paper introduces a reliability-regulated trajectory optimization framework for progressive COLMAP‑free 3D Gaussian Splatting (3DGS). It uses a self‑supervised bidirectional cycle‑consistency mechanism to control camera trajectory estimation through forward motion propagation and retrospective trajectory correction, thereby reducing error compounding without external priors. Experiments on Tanks and Temples and CO3D‑V2 demonstrate improved camera trajectory accuracy and novel‑view rendering quality compared to existing unposed baselines.
By Zijian Wu, Jinliang Wang, Zidian Lin, Ying Song, Ziqian Lu, Hanjie Ma, Zhen Ye, Mingfeng Jiang
arXiv:2609.17387v1 Announce Type: new
Abstract: Real-time dense SLAM is a core capability for robotics applications that require robust localization and high- quality mapping in dynamic or fast-chang...
By Yongqi Mao, Hao Shi, Yufan Zhang, Zhonghua Yi, Xiangfei Guo, Kaiwei Wang
arXiv:2607.24495v2 Announce Type: replace
Abstract: Structured-light (SL) cameras power depth sensing in millions of devices, and recent neural SL decoding methods have substantially improved their d...
By Jiaheng Li, Binsheng Zhang, Xinhai Chang, Wenzheng Chen
arXiv:2609.38054v1 Announce Type: cross
Abstract: We present Pow3R-SLAM, a real-time RGB-D simultaneous localization and mapping (SLAM) system that uses Pow3R for tracking and mapping. Inspired by MA...
By Christopher Kolios, Ishaan Mehta, Sasa Janjic, Yeganeh Bahoo, Sajad Saeedi
The paper introduces TempLoc, a Temporal‑aware Localization framework that improves outdoor LiDAR relocalization by leveraging spatio‑temporal consistency across scans. It first predicts point‑wise global coordinates with uncertainties, then estimates inter‑frame correspondences using an attention‑based Prior Coordinate Generation module, and finally fuses these predictions in an uncertainty‑guided manner to produce a more accurate global 6‑DoF pose. Experiments on the NCLT and Oxford RobotCar datasets show that TempLoc significantly outperforms existing state‑of‑the‑art methods.
By Minghang Zhu, Zhijing Wang, Yuxin Guo, Chen Liu, Yongshu Huang, Wen Li, Sheng Ao, Cheng Wang