104 citations · 194 across the 12 of their papers we have counts for
12 papers
Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection
Shichao Li, Peiliang Li, Qing Lian +2
Perceiving pedestrians in highly crowded urban environments is a difficult long-tail problem for learning-based autonomous perception. Speeding up 3D ground truth generation for su…
Open-world Semantic Segmentation for LIDAR Point Clouds
Jun Cen, Peng Yun, Shiwei Zhang +5
Current methods for LIDAR semantic segmentation are not robust enough for real-world applications, e.g., autonomous driving, since it is closed-set and static. The closed-set assum…
Open-set 3D Object Detection
Jun Cen, Peng Yun, Junhao Cai +2
3D object detection has been wildly studied in recent years, especially for robot perception systems. However, existing 3D object detection is under a closed-set condition, meaning…
Deep Metric Learning for Open World Semantic Segmentation
Jun Cen, Peng Yun, Junhao Cai +2
Classical close-set semantic segmentation networks have limited ability to detect out-of-distribution (OOD) objects, which is important for safety-critical applications such as aut…
Greedy-Based Feature Selection for Efficient LiDAR SLAM
Jianhao Jiao, Yilong Zhu, Haoyang Ye +5
Modern LiDAR-SLAM (L-SLAM) systems have shown excellent results in large-scale, real-world scenarios. However, they commonly have a high latency due to the expensive data associati…
Smart-Inspect: Micro Scale Localization and Classification of Smartphone Glass Defects for Industrial Automation
M Usman Maqbool Bhutta, Shoaib Aslam, Peng Yun +2
The presence of any type of defect on the glass screen of smart devices has a great impact on their quality. We present a robust semi-supervised learning framework for intelligent…
MLOD: Awareness of Extrinsic Perturbation in Multi-LiDAR 3D Object Detection for Autonomous Driving
Jianhao Jiao, Peng Yun, Lei Tai +1
Extrinsic perturbation always exists in multiple sensors. In this paper, we focus on the extrinsic uncertainty in multi-LiDAR systems for 3D object detection. We first analyze the…
The Role of the Hercules Autonomous Vehicle During the COVID-19 Pandemic: An Autonomous Logistic Vehicle for Contactless Goods Transportation
Tianyu Liu, Qinghai Liao, Lu Gan +28
Since early 2020, the coronavirus disease 2019 (COVID-19) has spread rapidly across the world. As at the date of writing this article, the disease has been globally reported in 223…
Visual-based Autonomous Driving Deployment from a Stochastic and Uncertainty-aware Perspective
Lei Tai, Peng Yun, Yuying Chen +3
End-to-end visual-based imitation learning has been widely applied in autonomous driving. When deploying the trained visual-based driving policy, a deterministic command is usually…
Focal Loss in 3D Object Detection
Peng Yun, Lei Tai, Yuan Wang +2
3D object detection is still an open problem in autonomous driving scenes. When recognizing and localizing key objects from sparse 3D inputs, autonomous vehicles suffer from a larg…
PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point Cloud
Yuan Wang, Tianyue Shi, Peng Yun +2
In this paper, we propose PointSeg, a real-time end-to-end semantic segmentation method for road-objects based on spherical images. We take the spherical image, which is transforme…
VR-Goggles for Robots: Real-to-sim Domain Adaptation for Visual Control
Jingwei Zhang, Lei Tai, Peng Yun +4
In this paper, we deal with the reality gap from a novel perspective, targeting transferring Deep Reinforcement Learning (DRL) policies learned in simulated environments to the rea…