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

Senthil Yogamani, Christian Witt, Hazem Rashed, Sanjaya Nayak, Saquib Mansoor, Padraig Varley, Xavier Perrotton, Derek Odea, Patrick Perez, Ciaran Hughes, Jonathan Horgan, Ganesh Sistu, Sumanth Chennupati, Michal Uricar, Stefan Milz, Martin Simon, Karl Amende

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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. 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. With WoodScape, we would like to encourage the community to adapt computer vision models for fisheye camera instead of using naive rectification.

Original languageEnglish
Title of host publicationProceedings - 2019 International Conference on Computer Vision, ICCV 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages9307-9317
Number of pages11
ISBN (Electronic)9781728148038
DOIs
Publication statusPublished - Oct 2019
Event17th IEEE/CVF International Conference on Computer Vision, ICCV 2019 - Seoul, Korea, Republic of
Duration: 27 Oct 20192 Nov 2019

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
Volume2019-October
ISSN (Print)1550-5499

Conference

Conference17th IEEE/CVF International Conference on Computer Vision, ICCV 2019
Country/TerritoryKorea, Republic of
CitySeoul
Period27/10/192/11/19

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