activity
20172021
most citedMulti-Task Learning for Segmentation of Building Footprints with Deep Neural Networks

40 citations · 40 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2021

RapidAI4EO: A Corpus for Higher Spatial and Temporal Reasoning

Giovanni Marchisio, Patrick Helber, Benjamin Bischke +5

Under the sponsorship of the European Union Horizon 2020 program, RapidAI4EO will establish the foundations for the next generation of Copernicus Land Monitoring Service (CLMS) pro…

cs.CV2020

Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory

Fatemeh Azimi, Benjamin Bischke, Sebastian Palacio +3

Video Object Segmentation (VOS) is an active research area of the visual domain. One of its fundamental sub-tasks is semi-supervised / one-shot learning: given only the segmentatio…

cs.CV2018

MultiNet: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery

Tim G. J. Rudner, Marc Rußwurm, Jakub Fil +4

We propose a novel approach for rapid segmentation of flooded buildings by fusing multiresolution, multisensor, and multitemporal satellite imagery in a convolutional neural networ…

cs.CV2018

Overcoming Missing and Incomplete Modalities with Generative Adversarial Networks for Building Footprint Segmentation

Benjamin Bischke, Patrick Helber, Florian König +2

The integration of information acquired with different modalities, spatial resolution and spectral bands has shown to improve predictive accuracies. Data fusion is therefore one of…

cs.CV201740 cited

Multi-Task Learning for Segmentation of Building Footprints with Deep Neural Networks

Benjamin Bischke, Patrick Helber, Joachim Folz +2

The increased availability of high resolution satellite imagery allows to sense very detailed structures on the surface of our planet. Access to such information opens up new direc…