6 papers
From Routes to Steps: Separating Semantic Progress from Local Execution in Vision-and-Language Navigation
Xiangyun Huang, Xiangchen Wang, Runfeng Lin +5
Vision-and-Language Navigation (VLN) requires an agent to follow a route-level instruction by executing its constituent steps from egocentric visual observations. Existing VLM-base…
Mesh-Learner: Texturing Mesh with Spherical Harmonics
Yunfei Wan, Jianheng Liu, Chunran Zheng +2
In this paper, we present a 3D reconstruction and rendering framework termed Mesh-Learner that is natively compatible with traditional rasterization pipelines. It integrates mesh a…
GS-SDF: LiDAR-Augmented Gaussian Splatting and Neural SDF for Geometrically Consistent Rendering and Reconstruction
Jianheng Liu, Yunfei Wan, Bowen Wang +3
Digital twins are fundamental to the development of autonomous driving and embodied artificial intelligence. However, achieving high-granularity surface reconstruction and high-fid…
An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization
Changhong Lin, Jiarong Lin, Zhiqiang Sui +4
Multi-sensor fusion is essential for autonomous vehicle localization, as it is capable of integrating data from various sources for enhanced accuracy and reliability. The accuracy…
Visual Localization in 3D Maps: Comparing Point Cloud, Mesh, and NeRF Representations
Lintong Zhang, Yifu Tao, Jiarong Lin +2
Recent advances in mapping techniques have enabled the creation of highly accurate dense 3D maps during robotic missions, such as point clouds, meshes, or NeRF-based representation…
Voxel-SLAM: A Complete, Accurate, and Versatile LiDAR-Inertial SLAM System
Zheng Liu, Haotian Li, Chongjian Yuan +7
In this work, we present Voxel-SLAM: a complete, accurate, and versatile LiDAR-inertial SLAM system that fully utilizes short-term, mid-term, long-term, and multi-map data associat…