TY - GEN
T1 - WoodScape
T2 - 17th IEEE/CVF International Conference on Computer Vision, ICCV 2019
AU - Yogamani, Senthil
AU - Witt, Christian
AU - Rashed, Hazem
AU - Nayak, Sanjaya
AU - Mansoor, Saquib
AU - Varley, Padraig
AU - Perrotton, Xavier
AU - Odea, Derek
AU - Perez, Patrick
AU - Hughes, Ciaran
AU - Horgan, Jonathan
AU - Sistu, Ganesh
AU - Chennupati, Sumanth
AU - Uricar, Michal
AU - Milz, Stefan
AU - Simon, Martin
AU - Amende, Karl
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85081934768&partnerID=8YFLogxK
U2 - 10.1109/ICCV.2019.00940
DO - 10.1109/ICCV.2019.00940
M3 - Conference contribution
AN - SCOPUS:85081934768
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 9307
EP - 9317
BT - Proceedings - 2019 International Conference on Computer Vision, ICCV 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 October 2019 through 2 November 2019
ER -