260 citations · 1.4k across the 56 of their papers we have counts for
8 papers · 2 filters
Graph Attention Layer Evolves Semantic Segmentation for Road Pothole Detection: A Benchmark and Algorithms
Rui Fan, Hengli Wang, Yuan Wang +2
Existing road pothole detection approaches can be classified as computer vision-based or machine learning-based. The former approaches typically employ 2-D image analysis/understan…
SCV-Stereo: Learning Stereo Matching from a Sparse Cost Volume
Hengli Wang, Rui Fan, Ming Liu
Convolutional neural network (CNN)-based stereo matching approaches generally require a dense cost volume (DCV) for disparity estimation. However, generating such cost volumes is c…
Co-Teaching: An Ark to Unsupervised Stereo Matching
Hengli Wang, Rui Fan, Ming Liu
Stereo matching is a key component of autonomous driving perception. Recent unsupervised stereo matching approaches have received adequate attention due to their advantage of not r…
SNE-RoadSeg+: Rethinking Depth-Normal Translation and Deep Supervision for Freespace Detection
Hengli Wang, Rui Fan, Peide Cai +1
Freespace detection is a fundamental component of autonomous driving perception. Recently, deep convolutional neural networks (DCNNs) have achieved impressive performance for this…
iCurb: Imitation Learning-based Detection of Road Curbs using Aerial Images for Autonomous Driving
Zhenhua Xu, Yuxiang Sun, Ming Liu
Detection of road curbs is an essential capability for autonomous driving. It can be used for autonomous vehicles to determine drivable areas on roads. Usually, road curbs are dete…
PVStereo: Pyramid Voting Module for End-to-End Self-Supervised Stereo Matching
Hengli Wang, Rui Fan, Peide Cai +1
Supervised learning with deep convolutional neural networks (DCNNs) has seen huge adoption in stereo matching. However, the acquisition of large-scale datasets with well-labeled gr…
Dynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and Algorithms
Hengli Wang, Rui Fan, Yuxiang Sun +1
Joint detection of drivable areas and road anomalies is very important for mobile robots. Recently, many semantic segmentation approaches based on convolutional neural networks (CN…
Ground-aware Monocular 3D Object Detection for Autonomous Driving
Yuxuan Liu, Yuan Yixuan, Ming Liu
Estimating the 3D position and orientation of objects in the environment with a single RGB camera is a critical and challenging task for low-cost urban autonomous driving and mobil…