10 papers
CoMo3R-SLAM: Collaborative Monocular Dense SLAM with Learned 3D Reconstruction Priors for Outdoor Multi-Agent Systems
Zhihao Cao, Qi Shao, Shuhao Zhai +4
Collaborative dense SLAM is essential for multi-robot teams to achieve scalable and consistent 3D perception across large-scale outdoor environments. Existing systems typically dep…
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…
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…
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…