21 citations · 21 across the 3 of their papers we have counts for
8 papers
Meta-Learning for Few-Shot Land Cover Classification
Marc Rußwurm, Sherrie Wang, Marco Körner +1
The representations of the Earth's surface vary from one geographic region to another. For instance, the appearance of urban areas differs between continents, and seasonality influ…
A Generalized Multi-Task Learning Approach to Stereo DSM Filtering in Urban Areas
Lukas Liebel, Ksenia Bittner, Marco Körner
City models and height maps of urban areas serve as a valuable data source for numerous applications, such as disaster management or city planning. While this information is not gl…
Enhancing Traffic Scene Predictions with Generative Adversarial Networks
Peter König, Sandra Aigner, Marco Körner
We present a new two-stage pipeline for predicting frames of traffic scenes where relevant objects can still reliably be detected. Using a recent video prediction network, we first…
Early Classification for Agricultural Monitoring from Satellite Time Series
Marc Rußwurm, Romain Tavenard, Sébastien Lefèvre +1
In this work, we introduce a recently developed early classification mechanism to satellite-based agricultural monitoring. It augments existing classification models by an addition…
MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and Classification
Lukas Liebel, Marco Körner
We introduce MultiDepth, a novel training strategy and convolutional neural network (CNN) architecture that allows approaching single-image depth estimation (SIDE) as a multi-task…
Late or Earlier Information Fusion from Depth and Spectral Data? Large-Scale Digital Surface Model Refinement by Hybrid-cGAN
Ksenia Bittner, Marco Körner, Peter Reinartz
We present the workflow of a DSM refinement methodology using a Hybrid-cGAN where the generative part consists of two encoders and a common decoder which blends the spectral and he…