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  1. Z

    OSCAR: Occluded Stereo dataset for Convolutional Architectures with...

    • data.niaid.nih.gov
    • zenodo.org
    Updated Dec 31, 2021
    + more versions
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    Jochen Triesch (2021). OSCAR: Occluded Stereo dataset for Convolutional Architectures with Recurrence [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_3540899
    Explore at:
    Dataset updated
    Dec 31, 2021
    Dataset provided by
    Markus Roland Ernst
    Thomas Burwick
    Jochen Triesch
    Description

    OSCAR, the Occluded Stereo dataset for Convolutional Architectures with Recurrence. Version: 2.0 (dataset as presented in our JOV 2021 journal publication "Recurrent Processing Improves Occluded Object Recognition and Gives Rise to Perceptual Hysteresis")

    If you make use of the dataset, please cite as follows:

    Ernst, M. R., Burwick, T., & Triesch, J. (2021). Recurrent Processing Improves Occluded Object Recognition and Gives Rise to Perceptual Hysteresis. In Journal of Vision

    Contents

    readme.md - detailed description and sample pictures

    img.zip - folder that contains images for the readme file

    licence.md - licence agreement for using the datasets

    os-fmnist2c.zip - compressed archive of the occluded stereo FashionMNIST dataset (centered, ~1.1GB)

    os-fmnist2r.zip - compressed archive of the occluded stereo FashionMNIST dataset (random, ~1.2GB)

    os-mnist2c.zip - compressed archive of the occluded stereo MNIST dataset (centered, ~865MB)

    os-mnist2r.zip - compressed archive of the occluded stereo MNIST dataset (random, ~851MB)

    os-ycb2.zip - compressed archive of the occluded stereo ycb-object dataset (~1.1GB)

    os-ycb2_highres.zip - compressed archive of the occluded stereo ycb-object dataset (high resolution, ~9.8GB)

    OSCARv2_dataset.py - python script to directly load image data from folder, pytorch dataset

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Jochen Triesch (2021). OSCAR: Occluded Stereo dataset for Convolutional Architectures with Recurrence [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_3540899

OSCAR: Occluded Stereo dataset for Convolutional Architectures with Recurrence

Explore at:
Dataset updated
Dec 31, 2021
Dataset provided by
Markus Roland Ernst
Thomas Burwick
Jochen Triesch
Description

OSCAR, the Occluded Stereo dataset for Convolutional Architectures with Recurrence. Version: 2.0 (dataset as presented in our JOV 2021 journal publication "Recurrent Processing Improves Occluded Object Recognition and Gives Rise to Perceptual Hysteresis")

If you make use of the dataset, please cite as follows:

Ernst, M. R., Burwick, T., & Triesch, J. (2021). Recurrent Processing Improves Occluded Object Recognition and Gives Rise to Perceptual Hysteresis. In Journal of Vision

Contents

readme.md - detailed description and sample pictures

img.zip - folder that contains images for the readme file

licence.md - licence agreement for using the datasets

os-fmnist2c.zip - compressed archive of the occluded stereo FashionMNIST dataset (centered, ~1.1GB)

os-fmnist2r.zip - compressed archive of the occluded stereo FashionMNIST dataset (random, ~1.2GB)

os-mnist2c.zip - compressed archive of the occluded stereo MNIST dataset (centered, ~865MB)

os-mnist2r.zip - compressed archive of the occluded stereo MNIST dataset (random, ~851MB)

os-ycb2.zip - compressed archive of the occluded stereo ycb-object dataset (~1.1GB)

os-ycb2_highres.zip - compressed archive of the occluded stereo ycb-object dataset (high resolution, ~9.8GB)

OSCARv2_dataset.py - python script to directly load image data from folder, pytorch dataset

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