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.
The data article describes the Road Damage Dataset, RDD2022, which comprises 47, 420 road images from six countries, Japan, India, the Czech Republic, Norway, the United States, and China.
In total, 121 teams from several countries registered for this competition.
Lastly, we provide recommendations for readers, local agencies, and municipalities of other countries when one other country publishes its data and model for automatic road damage detection and classification.
Large mobility datasets collected from various sources have allowed us to observe, analyze, predict and solve a wide range of important urban challenges.
In this paper, we investigate state-of-the-art methods for counting pedestrians and the related performance of aerial footage.
This dataset is composed of 9, 053 road damage images captured with a smartphone installed on a car, with 15, 435 instances of road surface damage included in these road images.