RDD2022 - The multi-national Road Damage Dataset released through CRDDC'2022

D Arya, Hiroya Maeda, Yoshihide Sekimoto, Hiroshi Omata, Sanjay Kumar Ghosh, Durga Toshniwal, Madhavendra Sharma, Van Vung Pham, Jingtao Zhong, Muneer Al-Hammadi, Mamoona Birkhez Shami, Du Nguyen, Hanglin Cheng, Jing Zhang, Alex Klein-Paste, Helge Mork, Frank Lindseth, Toshikazu Seto, Alexander Mraz & Takehiro Kashiyama
Description The Road Damage Dataset, RDD2022, is released as a part of the Crowdsensing-based Road Damage Detection Challenge (CRDDC'2022), an IEEE BigData Cup. It comprises 47,420 road images from six countries, Japan, India, the Czech Republic, Norway, the United States, and China. The images have been annotated with more than 55,000 instances of road damage. Four types of road damage, namely longitudinal cracks, transverse cracks, alligator cracks, and potholes, are captured in the dataset....
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