373 citations · 1.4k across the 19 of their papers we have counts for
7 papers · 1 filter
Convolutional LSTMs for Cloud-Robust Segmentation of Remote Sensing Imagery
Marc Rußwurm, Marco Körner
Clouds frequently cover the Earth's surface and pose an omnipresent challenge to optical Earth observation methods. The vast majority of remote sensing approaches either selectivel…
Towards Multi-class Object Detection in Unconstrained Remote Sensing Imagery
Seyed Majid Azimi, Eleonora Vig, Reza Bahmanyar +2
Automatic multi-class object detection in remote sensing images in unconstrained scenarios is of high interest for several applications including traffic monitoring and disaster ma…
Auxiliary Tasks in Multi-task Learning
Lukas Liebel, Marco Körner
Multi-task convolutional neural networks (CNNs) have shown impressive results for certain combinations of tasks, such as single-image depth estimation (SIDE) and semantic segmentat…
Evaluation of CNN-based Single-Image Depth Estimation Methods
Tobias Koch, Lukas Liebel, Friedrich Fraundorfer +1
While an increasing interest in deep models for single-image depth estimation methods can be observed, established schemes for their evaluation are still limited. We propose a set…
Aerial LaneNet: Lane Marking Semantic Segmentation in Aerial Imagery using Wavelet-Enhanced Cost-sensitive Symmetric Fully Convolutional Neural Networks
Seyed Majid Azimi, Peter Fischer, Marco Körner +1
The knowledge about the placement and appearance of lane markings is a prerequisite for the creation of maps with high precision, necessary for autonomous driving, infrastructure m…
Building Instance Classification Using Street View Images
Jian Kang, Marco Körner, Yuanyuan Wang +2
Land-use classification based on spaceborne or aerial remote sensing images has been extensively studied over the past decades. Such classification is usually a patch-wise or pixel…