3 citations · 7 across the 5 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…