Self-Supervised Learning for Stereo Reconstruction on Aerial Images

Publikation: KonferenzbeitragPaperForschungBegutachtung

Abstract

Recent developments established deep learning as an inevitable tool to boost the performance of dense matching and stereo estimation. On the downside, learning these networks requires a substantial amount of training data to be successful. Consequently, the application of these models outside of the laboratory is far from straight forward. In this work we propose a self-supervised training procedure that allows us
to adapt our network to the specific (imaging) characteristics of the dataset at hand, without the requirement of external ground truth data. We instead generate interim training data by running our intermediate network on the whole dataset, followed by conservative outlier filtering. Bootstrapped from a pre-trained version of our hybrid CNN-CRF model, we alternate the generation of training data and network training.
With this simple concept we are able to lift the completeness and accuracy of the pretrained version significantly. We also show that our final model compares favorably to other popular stereo estimation algorithms on an aerial dataset.
Originalspracheenglisch
PublikationsstatusVeröffentlicht - 22 Jul 2018
Veranstaltung38th International Geoscience and Remote Sensing Symposium - Valencia, Valencia, Spanien
Dauer: 22 Jul 201827 Jul 2018
https://igarss2018.org

Konferenz

Konferenz38th International Geoscience and Remote Sensing Symposium
KurztitelIGARSS
LandSpanien
OrtValencia
Zeitraum22/07/1827/07/18
Internetadresse

Fingerprint

Supervised learning
Antennas
Imaging techniques

Schlagwörter

    Dies zitieren

    Knöbelreiter, P., Vogel, C., & Pock, T. (2018). Self-Supervised Learning for Stereo Reconstruction on Aerial Images. Beitrag in 38th International Geoscience and Remote Sensing Symposium, Valencia, Spanien.

    Self-Supervised Learning for Stereo Reconstruction on Aerial Images. / Knöbelreiter, Patrick; Vogel, Christoph; Pock, Thomas.

    2018. Beitrag in 38th International Geoscience and Remote Sensing Symposium, Valencia, Spanien.

    Publikation: KonferenzbeitragPaperForschungBegutachtung

    Knöbelreiter, P, Vogel, C & Pock, T 2018, 'Self-Supervised Learning for Stereo Reconstruction on Aerial Images' Beitrag in, Valencia, Spanien, 22/07/18 - 27/07/18, .
    Knöbelreiter P, Vogel C, Pock T. Self-Supervised Learning for Stereo Reconstruction on Aerial Images. 2018. Beitrag in 38th International Geoscience and Remote Sensing Symposium, Valencia, Spanien.
    Knöbelreiter, Patrick ; Vogel, Christoph ; Pock, Thomas. / Self-Supervised Learning for Stereo Reconstruction on Aerial Images. Beitrag in 38th International Geoscience and Remote Sensing Symposium, Valencia, Spanien.
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