Biased Cars Dataset
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
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Title |
Biased Cars Dataset
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Identifier |
https://doi.org/10.7910/DVN/F1NQ3R
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Creator |
Madan, Spandan
Henry, Timothy Dozier, Jamell Ho, Helen Bhandari, Nishchal Sasaki, Tomotake Durand, Fredo Pfister, Hanspeter Boix, Xavier |
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Publisher |
Harvard Dataverse
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Description |
We introduce a challenging, photo-realistic dataset for analyzing out-of-distribution performance in computer vision: the Biased-Cars dataset. Our dataset features outdoor scene data with fine control over scene clutter (trees, street furniture, and pedestrians), car colors, object occlusions, diverse backgrounds (building/road textures) and lighting conditions (sky maps). Biased-Cars consists of 30K images of five different car models with different car colors seen from different viewpoints car colors varying between 0-90 degrees of azimuth, and 0-50 degrees of zenith across multiple scales. We provide labels for car model, color, viewpoint and scale. We also provide semantic label maps for background categories including road, sky, pavement, pedestrians, trees and buildings. Our dataset offers complete control over the joint distribution of categories, viewpoints, and other scene parameters, and the use of physically based rendering ensures photo-realism.
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Subject |
Computer and Information Science
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Language |
English
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Contributor |
Madan, Spandan
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