WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving

Fisheye cameras are commonly employed for obtaining a large field of view in surveillance, augmented reality and in particular automotive applications. In spite of their 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.

Released in: WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving

Source: arXiv - WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving

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Summary

Fisheye cameras are commonly employed for obtaining a large field of view in surveillance, augmented reality and in particular automotive applications. In spite of their 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.

100K

Images in dataset

2019

Year Released

Key Links & Stats

valeoai / WoodScape

@article{yogamani2019woodscape, title={WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving}, author={Yogamani, Senthil and Hughes, Ciar{\'a}n and Horgan, Jonathan and Sistu, Ganesh and Varley, Padraig and O'Dea, Derek and Uric{\'a}r, Michal and Milz, Stefan and Simon, Martin and Amende, Karl and others}, journal={arXiv preprint arXiv:1905.01489}, year={2019} }

scenebox

Modalities

  1. Video

Verticals

  1. A/V

ML Task

  1. Image Classification
  2. Object Detection

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