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Aerial Road Segmentation in the Presence of Topological Label Noise

Henry, Corentin and Fraundorfer, Friedrich and Vig, Eleonora (2021) Aerial Road Segmentation in the Presence of Topological Label Noise. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 2336-2343. ICPR 2020, 10.-15. Jan. 2021, Milan, Italy. doi: 10.1109/ICPR48806.2021.9412054.

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Official URL: https://ieeexplore.ieee.org/document/9412054


The availability of large-scale annotated datasets has enabled Fully-Convolutional Neural Networks to reach outstanding performance on road extraction in aerial images. However, high-quality pixel-level annotation is expensive to produce and even manually labeled data often contains topological errors. Trading off quality for quantity, many datasets rely on already available yet noisy labels, for example from OpenStreetMap. In this paper, we explore the training of custom U-Nets built with ResNet and DenseNet backbones using noise-aware losses that are robust towards label omission and registration noise. We perform an extensive evaluation of standard and noise-aware losses, including a novel Bootstrapped DICE-Coefficient loss, on two challenging road segmentation benchmarks. Our losses yield a consistent improvement in overall extraction quality and exhibit a strong capacity to cope with severe label noise. Our method generalizes well to two other fine-grained topology delineation tasks: surface crack detection for quality inspection and cell membrane extraction in electron microscopy imagery.

Item URL in elib:https://elib.dlr.de/136343/
Document Type:Conference or Workshop Item (Poster)
Title:Aerial Road Segmentation in the Presence of Topological Label Noise
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Henry, CorentinCorentin.henry (at) dlr.dehttps://orcid.org/0000-0002-4330-3058
Fraundorfer, Friedrichfriedrich.fraundorfer (at) dlr.dehttps://orcid.org/0000-0002-5805-8892
Vig, Eleonoraeleonov (at) amazon.comUNSPECIFIED
Date:January 2021
Journal or Publication Title:2020 25th International Conference on Pattern Recognition (ICPR)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
DOI :10.1109/ICPR48806.2021.9412054
Page Range:pp. 2336-2343
Keywords:label noise; road extraction; semantic segmentation; satellite imagery; aerial imagery
Event Title:ICPR 2020
Event Location:Milan, Italy
Event Type:international Conference
Event Dates:10.-15. Jan. 2021
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - NGC KoFiF, R - Artificial Intelligence
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Henry, Corentin
Deposited On:09 Oct 2020 09:37
Last Modified:25 Aug 2021 10:51

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