7 citations · 7 across the 1 of their papers we have counts for
10 papers
ProSGNeRF: Progressive Dynamic Neural Scene Graph with Frequency Modulated Foundation Model in Urban Scenes
Tianchen Deng, Yanbo Wang, Yejia Liu +5
Implicit neural representation has demonstrated promising results in 3D reconstruction on various scenes. However, existing approaches either struggle to model fast-moving objects…
Compact 3D Gaussian Splatting For Dense Visual SLAM
Tianchen Deng, Chang Nie, Shuhong Liu +6
Recent work has shown that 3D Gaussian-based SLAM enables high-quality reconstruction, accurate pose estimation, and real-time rendering of scenes. However, these approaches are bu…
An Efficient LiDAR-Camera Fusion Network for Multi-Class 3D Dynamic Object Detection and Trajectory Prediction
Yushen He, Lei Zhao, Tianchen Deng +2
Service mobile robots are often required to avoid dynamic objects while performing their tasks, but they usually have only limited computational resources. To further advance the p…
What Is The Best 3D Scene Representation for Robotics? From Geometric to Foundation Models
Tianchen Deng, Yue Pan, Shenghai Yuan +10
In this paper, we provide a comprehensive overview of existing scene representation methods for robotics, covering traditional representations such as point clouds, voxels, signed…
VPGS-SLAM: Voxel-based Progressive 3D Gaussian SLAM in Large-Scale Scenes
Tianchen Deng, Wenhua Wu, Junjie He +4
3D Gaussian Splatting has recently shown promising results in dense visual SLAM. However, existing 3DGS-based SLAM methods are all constrained to small-room scenarios and struggle…
MCN-SLAM: Multi-Agent Collaborative Neural SLAM with Hybrid Implicit Neural Scene Representation
Tianchen Deng, Guole Shen, Xun Chen +9
Neural implicit scene representations have recently shown promising results in dense visual SLAM. However, existing implicit SLAM algorithms are constrained to single-agent scenari…