WoodScape

by Senthil YogamaniResearch Only

WoodScape

Fisheye cameras are commonly employed for obtaining a large field of view in surveillance, augmented reality and in particular automotive applications. In spite of its prevalence, there are few public datasets for detailed evaluation of computer vision algorithms on fisheye images. We release the first extensive fisheye automotive dataset, WoodScape, named after Robert Wood who invented the fisheye camera in 1906. WoodScape comprises of four surround view cameras and nine tasks including segmentation, depth estimation, 3D bounding box detection and soiling detection. Semantic annotation of 40 classes at the instance level is provided for over 10,000 images and annotation for other tasks are provided for over 100,000 images. We would like to encourage the community to adapt computer vision models for fisheye camera instead of naive rectification. Release The dataset and code for baseline experiments will be provided in stages. First release is planned for ICCV 2019 (end of October).

Dataset Attributes

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TasksDetection, Segmentation, Monocular Depth Estimation, Visual Odometry, Visual SLAM, Motion Segmentation, Soiling Detection
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CategoriesAutonomous Vehicles, Self-Driving, Fisheye
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SensorRGB Camera, LiDAR. GNSS, IMU

Class Labels

Contruction And FenceFour WheelersTraffic SignsPoles And Other ObjectsGround MarkingsLanemarksSidewalkRoadSkyVegetationPersonFour Wheelers GroupsFour Wheelers HeavyAnimalsRiderTwo Wheelers