CROCO: CROSS-MODAL CONTRASTIVE LEARNING FOR LOCALIZATION OF EARTH OBSERVATION DATA
Abstract. It is of interest to localize a ground-based LiDAR point cloud on remote sensing imagery. In this work, we tackle a subtask of this problem, i.e. to map a digital elevation model (DEM) rasterized from aerial LiDAR point cloud on the aerial imagery. We proposed a contrastive learning-based method that trains on DEM and high-resolution optical imagery and experiment the framework on different data sampling strategies and hyperparameters. In the best scenario, the Top-1 score of 0.71 and Top-5 score of 0.81 are obtained. The proposed method is promising for feature learning from RGB and DEM for localization and is potentially applicable to other data sources too. Source code is released at https://github.com/wtseng530/AVLocalization.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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CROCO: CROSS-MODAL CONTRASTIVE LEARNING FOR LOCALIZATION OF EARTH OBSERVATION DATA ; volume:V-2-2022 ; year:2022 ; pages:415-421 ; extent:7
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; V-2-2022 (2022), 415-421 (gesamt 7)
- Creator
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Tseng, W.-H.
Lê, H.-A.
Boulch, A.
Lefèvre, S.
Tiede, D.
- DOI
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10.5194/isprs-annals-V-2-2022-415-2022
- URN
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urn:nbn:de:101:1-2022051905172806420656
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
- 15.08.2025, 7:28 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Tseng, W.-H.
- Lê, H.-A.
- Boulch, A.
- Lefèvre, S.
- Tiede, D.
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