Azimi, Seyedmajid and Henry, Corentin and Sommer, Lars and Schumann, Arne and Vig, Eleonora (2019) SkyScapes - Fine-Grained Semantic Understanding of Aerial Scenes. IEEE. ICCV 2019, 27.10.-02.11.2019, Seoul, Korea.
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Abstract
Understanding the complex urban infrastructure withcentimeter-level accuracy is essential for many applicationsfrom autonomous driving to mapping, infrastructure monitoring, and urban management. Aerial images providevaluable information over a large area instantaneously; nevertheless, no current dataset captures the complexityof aerial scenes at the level of granularity required byreal-world applications. To address this, we introduceSkyScapes, an aerial image dataset with highly-accurate,fine-grained annotations for pixel-level semantic labeling.SkyScapes provides annotations for 31 semantic categoriesranging from large structures, such as buildings, roadsand vegetation, to fine details, such as 12 (sub-)categories of lane markings. We have defined two main tasks onthis dataset: dense semantic segmentation and multi-classlane-marking prediction. We carry out extensive exper-iments to evaluate state-of-the-art segmentation methodson SkyScapes. Existing methods struggle to deal with thewide range of classes, object sizes, scales, and fine detailspresent. We therefore propose a novel multi-task model,which incorporates semantic edge detection and is bettertuned for feature extraction from a wide range of scales.This model achieves notable improvements over the base-lines in region outlines and level of detail on both tasks.
Item URL in elib: | https://elib.dlr.de/131251/ | ||||||||||||||||||
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Document Type: | Conference or Workshop Item (Speech, Poster) | ||||||||||||||||||
Title: | SkyScapes - Fine-Grained Semantic Understanding of Aerial Scenes | ||||||||||||||||||
Authors: |
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Date: | 2019 | ||||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||||
Open Access: | Yes | ||||||||||||||||||
Gold Open Access: | No | ||||||||||||||||||
In SCOPUS: | No | ||||||||||||||||||
In ISI Web of Science: | No | ||||||||||||||||||
Page Range: | pp. 1-11 | ||||||||||||||||||
Publisher: | IEEE | ||||||||||||||||||
Status: | Published | ||||||||||||||||||
Keywords: | Deep learning, Convolutional Neural Network, Segmentation, HD-Map | ||||||||||||||||||
Event Title: | ICCV 2019 | ||||||||||||||||||
Event Location: | Seoul, Korea | ||||||||||||||||||
Event Type: | international Conference | ||||||||||||||||||
Event Dates: | 27.10.-02.11.2019 | ||||||||||||||||||
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 | ||||||||||||||||||
Location: | Oberpfaffenhofen | ||||||||||||||||||
Institutes and Institutions: | Remote Sensing Technology Institute > Photogrammetry and Image Analysis | ||||||||||||||||||
Deposited By: | Bahmanyar, Gholamreza | ||||||||||||||||||
Deposited On: | 26 Nov 2019 15:01 | ||||||||||||||||||
Last Modified: | 03 Dec 2019 17:01 |
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