215 citations · 335 across the 26 of their papers we have counts for
21 papers · 1 filter
Optimizing the Placement of Roadside LiDARs for Autonomous Driving
Wentao Jiang, Hao Xiang, Xinyu Cai +5
Multi-agent cooperative perception is an increasingly popular topic in the field of autonomous driving, where roadside LiDARs play an essential role. However, how to optimize the p…
UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase
Youquan Liu, Runnan Chen, Xin Li +9
Point-, voxel-, and range-views are three representative forms of point clouds. All of them have accurate 3D measurements but lack color and texture information. RGB images are a n…
StreetSurf: Extending Multi-view Implicit Surface Reconstruction to Street Views
Jianfei Guo, Nianchen Deng, Xinyang Li +6
We present a novel multi-view implicit surface reconstruction technique, termed StreetSurf, that is readily applicable to street view images in widely-used autonomous driving datas…
Calib-Anything: Zero-training LiDAR-Camera Extrinsic Calibration Method Using Segment Anything
Zhaotong Luo, Guohang Yan, Yikang Li
The research on extrinsic calibration between Light Detection and Ranging(LiDAR) and camera are being promoted to a more accurate, automatic and generic manner. Since deep learning…
DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds
Tao Ma, Xuemeng Yang, Hongbin Zhou +9
Existing offboard 3D detectors always follow a modular pipeline design to take advantage of unlimited sequential point clouds. We have found that the full potential of offboard 3D…
AD-PT: Autonomous Driving Pre-Training with Large-scale Point Cloud Dataset
Jiakang Yuan, Bo Zhang, Xiangchao Yan +4
It is a long-term vision for Autonomous Driving (AD) community that the perception models can learn from a large-scale point cloud dataset, to obtain unified representations that c…
SUG: Single-dataset Unified Generalization for 3D Point Cloud Classification
Siyuan Huang, Bo Zhang, Botian Shi +3
Although Domain Generalization (DG) problem has been fast-growing in the 2D image tasks, its exploration on 3D point cloud data is still insufficient and challenged by more complex…
Uni3D: A Unified Baseline for Multi-dataset 3D Object Detection
Bo Zhang, Jiakang Yuan, Botian Shi +3
Current 3D object detection models follow a single dataset-specific training and testing paradigm, which often faces a serious detection accuracy drop when they are directly deploy…
LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion
Xin Li, Tao Ma, Yuenan Hou +8
LiDAR-camera fusion methods have shown impressive performance in 3D object detection. Recent advanced multi-modal methods mainly perform global fusion, where image features and poi…
SCPNet: Semantic Scene Completion on Point Cloud
Zhaoyang Xia, Youquan Liu, Xin Li +5
Training deep models for semantic scene completion (SSC) is challenging due to the sparse and incomplete input, a large quantity of objects of diverse scales as well as the inheren…
Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection
Jiakang Yuan, Bo Zhang, Xiangchao Yan +4
Unsupervised Domain Adaptation (UDA) technique has been explored in 3D cross-domain tasks recently. Though preliminary progress has been made, the performance gap between the UDA-b…
Rethinking Range View Representation for LiDAR Segmentation
Lingdong Kong, Youquan Liu, Runnan Chen +6
LiDAR segmentation is crucial for autonomous driving perception. Recent trends favor point- or voxel-based methods as they often yield better performance than the traditional range…
LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Driving
Xiang Li, Junbo Yin, Botian Shi +3
Image instance segmentation is a fundamental research topic in autonomous driving, which is crucial for scene understanding and road safety. Advanced learning-based approaches ofte…
CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP
Runnan Chen, Youquan Liu, Lingdong Kong +6
Contrastive Language-Image Pre-training (CLIP) achieves promising results in 2D zero-shot and few-shot learning. Despite the impressive performance in 2D, applying CLIP to help the…
UniDA3D: Unified Domain Adaptive 3D Semantic Segmentation Pipeline
Ben Fei, Siyuan Huang, Jiakang Yuan +5
State-of-the-art 3D semantic segmentation models are trained on off-the-shelf public benchmarks, but they will inevitably face the challenge of recognition accuracy drop when these…
Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection
Xin Li, Botian Shi, Yuenan Hou +4
Multi-modal 3D object detection has been an active research topic in autonomous driving. Nevertheless, it is non-trivial to explore the cross-modal feature fusion between sparse 3D…
Online LiDAR-Camera Extrinsic Parameters Self-checking
Pengjin Wei, Guohang Yan, Yikang Li +3
With the development of neural networks and the increasing popularity of automatic driving, the calibration of the LiDAR and the camera has attracted more and more attention. This…
Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentation
Yuenan Hou, Xinge Zhu, Yuexin Ma +2
This article addresses the problem of distilling knowledge from a large teacher model to a slim student network for LiDAR semantic segmentation. Directly employing previous distill…
Comprehensive Review of Deep Learning-Based 3D Point Cloud Completion Processing and Analysis
Ben Fei, Weidong Yang, Wenming Chen +5
Point cloud completion is a generation and estimation issue derived from the partial point clouds, which plays a vital role in the applications in 3D computer vision. The progress…
CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene
Pengjin Wei, Guohang Yan, Yikang Li +4
Sensor-based environmental perception is a crucial part of the autonomous driving system. In order to get an excellent perception of the surrounding environment, an intelligent sys…
Multi-modal Sensor Fusion for Auto Driving Perception: A Survey
Keli Huang, Botian Shi, Xiang Li +3
Multi-modal fusion is a fundamental task for the perception of an autonomous driving system, which has recently intrigued many researchers. However, achieving a rather good perform…