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    OmniCity

    • opendatalab.com
    zip
    Updated Oct 1, 2022
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    Sun Yat-Sen University (2022). OmniCity [Dataset]. https://opendatalab.com/CVeRS/OmniCity
    Explore at:
    zip(52831834416 bytes)Available download formats
    Dataset updated
    Oct 1, 2022
    Dataset provided by
    Sun Yat-Sen University
    Wuhan University
    Shanghai Artificial Intelligence Laboratory
    Chinese University of Hong Kong
    SenseTime Research
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    OmniCity is a new dataset for omnipotent city understanding from multi-level and multi-view images. The dataset contains multi-view satellite images as well as street-level panorama and mono-view image that are collected from 25K geo-locations in New York City, with pixel-wise annotations for a variety of tasks including building footprint extraction, height estimation, and building plane/instance/fine-grained segmentation.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Sun Yat-Sen University (2022). OmniCity [Dataset]. https://opendatalab.com/CVeRS/OmniCity

OmniCity

OpenDataLab/OmniCity

Explore at:
284 scholarly articles cite this dataset (View in Google Scholar)
zip(52831834416 bytes)Available download formats
Dataset updated
Oct 1, 2022
Dataset provided by
Sun Yat-Sen University
Wuhan University
Shanghai Artificial Intelligence Laboratory
Chinese University of Hong Kong
SenseTime Research
License

Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically

Description

OmniCity is a new dataset for omnipotent city understanding from multi-level and multi-view images. The dataset contains multi-view satellite images as well as street-level panorama and mono-view image that are collected from 25K geo-locations in New York City, with pixel-wise annotations for a variety of tasks including building footprint extraction, height estimation, and building plane/instance/fine-grained segmentation.

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