4 papers · 1 filter
A Comprehensive Survey on Deep Learning-Based LiDAR Super-Resolution for Autonomous Driving
June Moh Goo, Zichao Zeng, Jan Boehm
LiDAR sensors are often considered essential for autonomous driving, but high-resolution sensors remain expensive while affordable low-resolution sensors produce sparse point cloud…
Real-Time LiDAR Super-Resolution via Frequency-Aware Multi-Scale Fusion
June Moh Goo, Zichao Zeng, Jan Boehm
LiDAR super-resolution addresses the challenge of achieving high-quality 3D perception from cost-effective, low-resolution sensors. While recent transformer-based approaches like T…
Exploring Single Domain Generalization of LiDAR-based Semantic Segmentation under Imperfect Labels
Weitong Kong, Zichao Zeng, Di Wen +5
Accurate perception is critical for vehicle safety, with LiDAR as a key enabler in autonomous driving. To ensure robust performance across environments, sensor types, and weather c…
Hybrid-Segmentor: A Hybrid Approach to Automated Fine-Grained Crack Segmentation in Civil Infrastructure
June Moh Goo, Xenios Milidonis, Alessandro Artusi +2
Detecting and segmenting cracks in infrastructure, such as roads and buildings, is crucial for safety and cost-effective maintenance. In spite of the potential of deep learning, th…