1 citations · 1 across the 12 of their papers we have counts for
12 papers
Adaptive World Memory 3D Foundation Model for Scalable 3D Mapping, Localization, and Rendering
Tianchen Deng, Guole Shen, Yilin Shen +7
Recent 3D foundation models enable generalizable geometric reasoning from RGB images but remain limited in persistent memory, scalability, and renderable scene modeling. We present…
CoMo3R-SLAM: Collaborative Monocular Dense SLAM with Learned 3D Reconstruction Priors for Outdoor Multi-Agent Systems
Zhihao Cao, Qi Shao, Shuhao Zhai +4
Outdoor robot teams need a shared dense map despite limited overlap, independent reference frames, and uncertain monocular scale. Collaborative dense SLAM systems typically resolve…
MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction
Zhihao Cao, Qi Shao, Shuhao Zhai +4
Collaborative photorealistic 3D reconstruction from multiple agents enables rapid large-scale scene capture for virtual production and cooperative multi-robot exploration. While re…
OGScene3D: Incremental Open-Vocabulary 3D Gaussian Scene Graph Mapping for Scene Understanding
Siting Zhu, Ziyun Lu, Guangming Wang +5
Open-vocabulary scene understanding is crucial for robotic applications, enabling robots to comprehend complex 3D environmental contexts and supporting various downstream tasks suc…
Dream-SLAM: Dreaming the Unseen for Active SLAM in Dynamic Environments
Xiangqi Meng, Pengxu Hou, Zhenjun Zhao +4
In addition to the core tasks of simultaneous localization and mapping (SLAM), active SLAM additionally in- volves generating robot actions that enable effective and efficient expl…
WeatherCity: Urban Scene Reconstruction with Controllable Multi-Weather Transformation
Wenhua Wu, Huai Guan, Zhe Liu +1
Editable high-fidelity 4D scenes are crucial for autonomous driving, as they can be applied to end-to-end training and closed-loop simulation. However, existing reconstruction meth…
DGSLAM: 4D Dynamic Gaussian Splatting SLAM
Siting Zhu, Yuxiang Huang, Wenhua Wu +4
Recent advances in Dense Simultaneous Localization and Mapping (SLAM) have demonstrated remarkable performance in static environments. However, dense SLAM in dynamic environments r…
S-MLLM: Boosting Spatial Reasoning Capability of MLLMs for 3D Visual Grounding with Structural Guidance
Beining Xu, Siting Zhu, Zhao Jin +2
3D Visual Grounding (3DVG) focuses on locating objects in 3D scenes based on natural language descriptions, serving as a fundamental task for embodied AI and robotics. Recent advan…
SGLoc: Semantic Localization System for Camera Pose Estimation from 3D Gaussian Splatting Representation
Beining Xu, Siting Zhu, Hesheng Wang
We propose SGLoc, a novel localization system that directly regresses camera poses from 3D Gaussian Splatting (3DGS) representation by leveraging semantic information. Our method u…
KN-LIO: Geometric Kinematics and Neural Field Coupled LiDAR-Inertial Odometry
Zhong Wang, Lele Ren, Yue Wen +1
Recent advancements in LiDAR-Inertial Odometry (LIO) have boosted a large amount of applications. However, traditional LIO systems tend to focus more on localization rather than ma…
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…