4.7k citations · 6.6k across the 79 of their papers we have counts for
23 papers · 1 filter
MacFormer: Map-Agent Coupled Transformer for Real-time and Robust Trajectory Prediction
Chen Feng, Hangning Zhou, Huadong Lin +5
Predicting the future behavior of agents is a fundamental task in autonomous vehicle domains. Accurate prediction relies on comprehending the surrounding map, which significantly r…
G3Reg: Pyramid Graph-based Global Registration using Gaussian Ellipsoid Model
Zhijian Qiao, Zehuan Yu, Binqian Jiang +2
This study introduces a novel framework, G3Reg, for fast and robust global registration of LiDAR point clouds. In contrast to conventional complex keypoints and descriptors, we ext…
Towards View-invariant and Accurate Loop Detection Based on Scene Graph
Chuhao Liu, Shaojie Shen
Loop detection plays a key role in visual Simultaneous Localization and Mapping (SLAM) by correcting the accumulated pose drift. In indoor scenarios, the richly distributed semanti…
Are All Point Clouds Suitable for Completion? Weakly Supervised Quality Evaluation Network for Point Cloud Completion
Jieqi Shi, Peiliang Li, Xiaozhi Chen +1
In the practical application of point cloud completion tasks, real data quality is usually much worse than the CAD datasets used for training. A small amount of noisy data will usu…
The Devil is in the Wrongly-classified Samples: Towards Unified Open-set Recognition
Jun Cen, Di Luan, Shiwei Zhang +5
Open-set Recognition (OSR) aims to identify test samples whose classes are not seen during the training process. Recently, Unified Open-set Recognition (UOSR) has been proposed to…
You Only Label Once: 3D Box Adaptation from Point Cloud to Image via Semi-Supervised Learning
Jieqi Shi, Peiliang Li, Xiaozhi Chen +1
The image-based 3D object detection task expects that the predicted 3D bounding box has a ``tightness'' projection (also referred to as cuboid), which fits the object contour well…
Temporal Point Cloud Completion with Pose Disturbance
Jieqi Shi, Lingyun Xu, Peiliang Li +2
Point clouds collected by real-world sensors are always unaligned and sparse, which makes it hard to reconstruct the complete shape of object from a single frame of data. In this w…
Event-based Motion Segmentation by Cascaded Two-Level Multi-Model Fitting
Xiuyuan Lu, Yi Zhou, Shaojie Shen
Among prerequisites for a synthetic agent to interact with dynamic scenes, the ability to identify independently moving objects is specifically important. From an application persp…
Event-based Motion Segmentation with Spatio-Temporal Graph Cuts
Yi Zhou, Guillermo Gallego, Xiuyuan Lu +2
Identifying independently moving objects is an essential task for dynamic scene understanding. However, traditional cameras used in dynamic scenes may suffer from motion blur or ex…
Tracking from Patterns: Learning Corresponding Patterns in Point Clouds for 3D Object Tracking
Jieqi Shi, Peiliang Li, Shaojie Shen
A robust 3D object tracker which continuously tracks surrounding objects and estimates their trajectories is key for self-driving vehicles. Most existing tracking methods employ a…
Event-based Stereo Visual Odometry
Yi Zhou, Guillermo Gallego, Shaojie Shen
Event-based cameras are bio-inspired vision sensors whose pixels work independently from each other and respond asynchronously to brightness changes, with microsecond resolution. T…
FP-Stereo: Hardware-Efficient Stereo Vision for Embedded Applications
Jieru Zhao, Tingyuan Liang, Liang Feng +4
Fast and accurate depth estimation, or stereo matching, is essential in embedded stereo vision systems, requiring substantial design effort to achieve an appropriate balance among…
Joint Spatial-Temporal Optimization for Stereo 3D Object Tracking
Peiliang Li, Jieqi Shi, Shaojie Shen
Directly learning multiple 3D objects motion from sequential images is difficult, while the geometric bundle adjustment lacks the ability to localize the invisible object centroid.…
PiP: Planning-informed Trajectory Prediction for Autonomous Driving
Haoran Song, Wenchao Ding, Yuxuan Chen +3
It is critical to predict the motion of surrounding vehicles for self-driving planning, especially in a socially compliant and flexible way. However, future prediction is challengi…
Flow-Motion and Depth Network for Monocular Stereo and Beyond
Kaixuan Wang, Shaojie Shen
We propose a learning-based method that solves monocular stereo and can be extended to fuse depth information from multiple target frames. Given two unconstrained images from a mon…
Multi-Sensor 3D Object Box Refinement for Autonomous Driving
Peiliang Li, Siqi Liu, Shaojie Shen
We propose a 3D object detection system with multi-sensor refinement in the context of autonomous driving. In our framework, the monocular camera serves as the fundamental sensor f…
Real-Time Dense Stereo Embedded in A UAV for Road Inspection
Rui Fan, Jianhao Jiao, Jie Pan +3
The condition assessment of road surfaces is essential to ensure their serviceability while still providing maximum road traffic safety. This paper presents a robust stereo vision…
Stereo R-CNN based 3D Object Detection for Autonomous Driving
Peiliang Li, Xiaozhi Chen, Shaojie Shen
We propose a 3D object detection method for autonomous driving by fully exploiting the sparse and dense, semantic and geometry information in stereo imagery. Our method, called Ste…
A General Optimization-based Framework for Global Pose Estimation with Multiple Sensors
Tong Qin, Shaozu Cao, Jie Pan +1
Accurate state estimation is a fundamental problem for autonomous robots. To achieve locally accurate and globally drift-free state estimation, multiple sensors with complementary…
A General Optimization-based Framework for Local Odometry Estimation with Multiple Sensors
Tong Qin, Jie Pan, Shaozu Cao +1
Nowadays, more and more sensors are equipped on robots to increase robustness and autonomous ability. We have seen various sensor suites equipped on different platforms, such as st…
Online Temporal Calibration for Monocular Visual-Inertial Systems
Tong Qin, Shaojie Shen
Accurate state estimation is a fundamental module for various intelligent applications, such as robot navigation, autonomous driving, virtual and augmented reality. Visual and iner…
Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving
Peiliang Li, Tong Qin, Shaojie Shen
We propose a stereo vision-based approach for tracking the camera ego-motion and 3D semantic objects in dynamic autonomous driving scenarios. Instead of directly regressing the 3D…
Relocalization, Global Optimization and Map Merging for Monocular Visual-Inertial SLAM
Tong Qin, Perliang Li, Shaojie Shen
The monocular visual-inertial system (VINS), which consists one camera and one low-cost inertial measurement unit (IMU), is a popular approach to achieve accurate 6-DOF state estim…