Multimodal Vision Research Laboratory

MVRL

view additional datasets released by my group.

Crossview USA (CVUSA)

Dataset Description

A large dataset containing millions of pairs of ground-level and aerial/satellite images from across the United States.

Dataset Download

The CVUSA dataset is available as five files form Google Drive.

This subset of CVUSA is often used for localization evaluation. If you use this subset, please also cite the Zhai et al. CVPR 2017 paper.

Disclaimer: The street-view panorama imagery is owned and copyrighted by Google Inc. The flickr images are owned by Flickr, Inc. The aerial images are from Bing Maps and are subject to their Terms of Service. For commercial usage of the dataset, one must seek explicit permissions from each of these rightful owners.

Dataset Citation

If you use the dataset, please cite the following publications:
  1. PDF Workman S, Souvenir R, Jacobs N. 2015. Wide-Area Image Geolocalization with Aerial Reference Imagery. In: IEEE International Conference on Computer Vision (ICCV). 1–9. DOI: 10.1109/ICCV.2015.451.
    bibtex | website | code | doi

Related Publication(s)

  1. PDF Salem T, Workman S, Jacobs N. 2020. Learning a Dynamic Map of Visual Appearance. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). DOI: 10.1109/CVPR42600.2020.01245.
    bibtex | website | doi
  2. Greenwell C, Workman S, Jacobs N. 2019. Implicit Land Use Mapping Using Social Media Imagery. In: IEEE Applied Imagery and Pattern Recognition (AIPR). DOI: 10.1109/AIPR47015.2019.9174570.
    bibtex | doi
  3. Salem T, Greenwell C, Blanton H, Jacobs N. 2019. Learning to Map Nearly Anything. In: IEEE International Geoscience and Remote Sensing Symposium (IGARSS). DOI: 10.1109/IGARSS.2019.8900646.
    bibtex | doi
  4. Greenwell C, Workman S, Jacobs N. 2018. What Goes Where: Predicting Object Distributions from Above. In: IEEE International Geoscience and Remote Sensing Symposium (IGARSS). DOI: 10.1109/IGARSS.2018.8519251.
    bibtex | website | doi
  5. PDF Zhai M, Bessinger Z, Workman S, Jacobs N. 2017. Predicting Ground-Level Scene Layout from Aerial Imagery. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). DOI: 10.1109/CVPR.2017.440.
    bibtex | code | doi
  6. PDF Workman S, Souvenir R, Jacobs N. 2015. Wide-Area Image Geolocalization with Aerial Reference Imagery. In: IEEE International Conference on Computer Vision (ICCV). 1–9. DOI: 10.1109/ICCV.2015.451.
    bibtex | website | code | doi
  7. PDF Workman S, Jacobs N. 2015. On the Location Dependence of Convolutional Neural Network Features. In: IEEE/ISPRS Workshop: Looking from above: When Earth observation meets vision (EARTHVISION). 1–9. DOI: 10.1109/CVPRW.2015.7301385.
    bibtex | doi