202 citations · 250 across the 11 of their papers we have counts for
11 papers
GPOcc++: Unified Sparse Gaussian Occupancy Prediction with Visual Geometry Priors
Changqing Zhou, Yueru Luo, Yulan Guo +3
Accurate 3D scene understanding is fundamental to embodied intelligence and autonomous driving, where 3D occupancy provides a unified representation of objects, structures, and fre…
Drone-NeRF: Efficient NeRF Based 3D Scene Reconstruction for Large-Scale Drone Survey
Zhihao Jia, Bing Wang, Changhao Chen
Neural rendering has garnered substantial attention owing to its capacity for creating realistic 3D scenes. However, its applicability to extensive scenes remains challenging, with…
Deep Learning for Visual Localization and Mapping: A Survey
Changhao Chen, Bing Wang, Chris Xiaoxuan Lu +2
Deep learning based localization and mapping approaches have recently emerged as a new research direction and receive significant attentions from both industry and academia. Instea…
Decoupling Skill Learning from Robotic Control for Generalizable Object Manipulation
Kai Lu, Bo Yang, Bing Wang +1
Recent works in robotic manipulation through reinforcement learning (RL) or imitation learning (IL) have shown potential for tackling a range of tasks e.g., opening a drawer or a c…
DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Images
Bing Wang, Lu Chen, Bo Yang
In this paper, we study the problem of 3D scene geometry decomposition and manipulation from 2D views. By leveraging the recent implicit neural representation techniques, particula…
BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework
Tingting Liang, Hongwei Xie, Kaicheng Yu +6
Fusing the camera and LiDAR information has become a de-facto standard for 3D object detection tasks. Current methods rely on point clouds from the LiDAR sensor as queries to lever…
RangeUDF: Semantic Surface Reconstruction from 3D Point Clouds
Bing Wang, Zhengdi Yu, Bo Yang +5
We present RangeUDF, a new implicit representation based framework to recover the geometry and semantics of continuous 3D scene surfaces from point clouds. Unlike occupancy fields…
No Pain, Big Gain: Classify Dynamic Point Cloud Sequences with Static Models by Fitting Feature-level Space-time Surfaces
Jia-Xing Zhong, Kaichen Zhou, Qingyong Hu +3
Scene flow is a powerful tool for capturing the motion field of 3D point clouds. However, it is difficult to directly apply flow-based models to dynamic point cloud classification…
CubeLearn: End-to-end Learning for Human Motion Recognition from Raw mmWave Radar Signals
Peijun Zhao, Chris Xiaoxuan Lu, Bing Wang +2
mmWave FMCW radar has attracted huge amount of research interest for human-centered applications in recent years, such as human gesture/activity recognition. Most existing pipeline…
3-D Motion Capture of an Unmodified Drone with Single-chip Millimeter Wave Radar
Peijun Zhao, Chris Xiaoxuan Lu, Bing Wang +2
Accurate motion capture of aerial robots in 3-D is a key enabler for autonomous operation in indoor environments such as warehouses or factories, as well as driving forward researc…
Learning Selective Sensor Fusion for States Estimation
Changhao Chen, Stefano Rosa, Chris Xiaoxuan Lu +3
Autonomous vehicles and mobile robotic systems are typically equipped with multiple sensors to provide redundancy. By integrating the observations from different sensors, these mob…