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データセットarXiv:1905.01489

WoodScape: 自動運転向けマルチタスク・マルチカメラ魚眼データセット

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

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自動運転向けに4台の魚眼カメラと9種類のタスク(セグメンテーション、深度推定、3D検出、汚れ検出など)を収録した初の大規模魚眼データセットを公開し、魚眼画像への直接適用を促す。

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

分類: cs.CV, cs.AI, cs.LG, cs.RO, stat.ML

原文アブストラクト

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.

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