Road Damage Detection
13 papers with code • 1 benchmarks • 3 datasets
Road damage detection is the task of detecting damage in roads.
( Image credit: Road Damage Detection And Classification In Smartphone Captured Images Using Mask R-CNN )
Libraries
Use these libraries to find Road Damage Detection models and implementations
RDD-2020
Pothole Mix
NPO
Latest papers with no code
Integrating GAN and Texture Synthesis for Enhanced Road Damage Detection
In addition to using GAN to generate damage with various shapes, we further employ texture synthesis techniques to extract road textures.
Crowdsensing-based Road Damage Detection Challenge (CRDDC-2022)
The Big Data Cup challenges involve a released dataset and a well-defined problem with clear evaluation metrics.
Road Damages Detection and Classification with YOLOv7
The results show that the data collection from Google Street View is efficient, and the proposed deep learning approach results in F1 scores of 81. 7% on the road damage data collected from the United States using Google Street View and 74. 1% on all test images of this dataset.
AI-Driven Road Maintenance Inspection v2: Reducing Data Dependency & Quantifying Road Damage
Road infrastructure maintenance inspection is typically a labor-intensive and critical task to ensure the safety of all road users.
Road Rutting Detection using Deep Learning on Images
The proposed road rutting dataset and the results of our research study will help accelerate the research on detection of road rutting using deep learning.
A Computer Vision-assisted Approach to Automated Real-Time Road Infrastructure Management
Accurate automated detection of road pavement distresses is critical for the timely identification and repair of potentially accident-inducing road hazards such as potholes and other surface-level asphalt cracks.
Global Road Damage Detection: State-of-the-art Solutions
In total, 121 teams from several countries registered for this competition.
Road Damage Detection Acquisition System based on Deep Neural Networks for Physical Asset Management
Research on damage detection of road surfaces has been an active area of re-search, but most studies have focused so far on the detection of the presence of damages.
