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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 …
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
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 …
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
Modern optical satellite sensors enable high-resolution stereo reconstruction from space.
But the challenging imaging conditions when observing the Earth from space push stereo …
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
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 …
quantitative study of crop growth. The segmentation and classification of crop point cloud …
Machine-learned 3d building vectorization from satellite imagery
We propose a machine learning based approach for automatic 3D building reconstruction
and vectorization. Taking a single-channel photogrammetric digital surface model (DSM) …
and vectorization. Taking a single-channel photogrammetric digital surface model (DSM) …
Real-gdsr: Real-world guided dsm super-resolution via edge-enhancing residual network
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 …
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 …
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
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 …
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
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 …
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
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 …
fundamental for remote sensing applications with the need for flexibility and fast response …