Road Surface Image Dataset with Detailed Annotations

Published: 9 May 2022| Version 1 | DOI: 10.17632/w86hvkrzc5.1
Contributors:
Tong Zhao,
yintao wei

Description

The preview of the road surface states is essential for improving the safety and the ride comfort of autonomous vehicles. This dataset consists of 370151 (240 x 360 pixels) road surface images captured under a wide range of road and weather conditions in China. The original pictures are acquired with a vehicle-mounted camera and then the patches containing only the road surface area are cropped. The images are classified into 27 categories, containing both the friction level, material, and unevenness properties. This large-scale dataset is useful for developing vision-based road sensing modules to improve the performance of the driving assistance systems.

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Institutions

Tsinghua University

Categories

Computer Vision, Intelligent Autonomous Vehicles, Autonomous Driving, Image Classification, Road Transportation

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