A review of 3D reconstruction from high-resolution urban satellite images

L Zhao, H Wang, Y Zhu, M Song - International Journal of Remote …, 2023‏ - Taylor & Francis
Automated 3D reconstruction based on satellite images has become a research hotspot at
the interdisciplinary of photogrammetry and computer vision. The 3D results based on …

[HTML][HTML] PLANES4LOD2: Reconstruction of LoD-2 building models using a depth attention-based fully convolutional neural network

P Schuegraf, J Shan, K Bittner - ISPRS Journal of Photogrammetry and …, 2024‏ - Elsevier
Abstract Level of detail (LoD)-2 reconstruction is an inevitable task in digital twin-related
applications such as disaster management, flood simulation, landslide simulation and solar …

[HTML][HTML] ResDepth: A deep residual prior for 3D reconstruction from high-resolution satellite images

C Stucker, K Schindler - ISPRS Journal of Photogrammetry and Remote …, 2022‏ - Elsevier
Modern optical satellite sensors enable high-resolution stereo reconstruction from space.
But the challenging imaging conditions when observing the Earth from space push stereo …

[HTML][HTML] Panicle-3D: Efficient phenoty** tool for precise semantic segmentation of rice panicle point cloud

L Gong, X Du, K Zhu, K Lin, Q Lou, Z Yuan… - Plant …, 2021‏ - spj.science.org
The automated measurement of crop phenotypic parameters is of great significance to the
quantitative study of crop growth. The segmentation and classification of crop point cloud …

Machine-learned 3d building vectorization from satellite imagery

Y Wang, S Zorzi, K Bittner - … of the IEEE/CVF Conference on …, 2021‏ - openaccess.thecvf.com
We propose a machine learning based approach for automatic 3D building reconstruction
and vectorization. Taking a single-channel photogrammetric digital surface model (DSM) …

Real-gdsr: Real-world guided dsm super-resolution via edge-enhancing residual network

D Panangian, K Bittner - ISPRS Annals of the Photogrammetry, Remote …, 2024‏ - elib.dlr.de
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 …

Semantic joint monocular remote sensing image digital surface model reconstruction based on feature multiplexing and inpainting

J Lu, Q Hu - IEEE Transactions on Geoscience and Remote …, 2022‏ - ieeexplore.ieee.org
Digital surface model (DSM) presents height information of the Earth's surface and plays an
important role in many remote sensing (RS) applications. Since the conventional acquisition …

Spatial interpolation of digital elevation model based on multi-scale conditional generative adversarial network with adaptive joint loss

Z Huo, J Yang, D Chen, L Zhang… - Journal of Applied …, 2025‏ - spiedigitallibrary.org
The digital elevation model (DEM) serves as a vital data source for surface 3D modeling.
Due to the limitations in sampling conditions and cost constraints, we usually obtain …

[HTML][HTML] Dual-stream spatiotemporal networks with feature sharing for monitoring animals in the home cage

EI Nwokedi, RS Bains, L Bidaut, X Ye, S Wells… - Sensors, 2023‏ - mdpi.com
This paper presents a spatiotemporal deep learning approach for mouse behavioral
classification in the home-cage. Using a series of dual-stream architectures with assorted …

Enhancing Building Shape Details Through Deep Learning in Single-Image SAR-Based DSM

K Bittner, M Recla, S Auer… - IGARSS 2024-2024 IEEE …, 2024‏ - ieeexplore.ieee.org
Due to the reliability of data acquisition, synthetic aperture radar (SAR) sensors are
fundamental for remote sensing applications with the need for flexibility and fast response …