no code implementations • 14 Apr 2024 • Vasudha Venkatesan, Daniel Panangian, Mario Fuentes Reyes, Ksenia Bittner
The use of synthetically generated images as an alternative, alleviates this problem but suffers from the problem of domain generalization.
no code implementations • 5 Apr 2024 • Daniel Panangian, Ksenia Bittner
A low-resolution digital surface model (DSM) features distinctive attributes impacted by noise, sensor limitations and data acquisition conditions, which failed to be replicated using simple interpolation methods like bicubic.
no code implementations • 13 Apr 2021 • Yi Wang, Stefano Zorzi, Ksenia Bittner
We propose a machine learning based approach for automatic 3D building reconstruction and vectorization.
no code implementations • 24 Jul 2020 • Stefano Zorzi, Ksenia Bittner, Friedrich Fraundorfer
In the fast developing countries it is hard to trace new buildings construction or old structures destruction and, as a result, to keep the up-to-date cadastre maps.
no code implementations • 24 Jul 2020 • Stefano Zorzi, Ksenia Bittner, Friedrich Fraundorfer
We propose a machine learning based approach for automatic regularization and polygonization of building segmentation masks.
no code implementations • 6 Apr 2020 • Lukas Liebel, Ksenia Bittner, Marco Körner
Such basic models can be filtered by convolutional neural networks (CNNs), trained on labels derived from digital elevation models (DEMs) and 3D city models, in order to obtain a refined DSM.
no code implementations • 22 Apr 2019 • 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 height information within one network.
1 code implementation • 8 Mar 2019 • Ksenia Bittner, Marco Körner, Peter Reinartz
We describe the workflow of a digital surface models (DSMs) refinement algorithm using a hybrid conditional generative adversarial network (cGAN) where the generative part consists of two parallel networks merged at the last stage forming a WNet architecture.