The paper presents a method for enhancing coarse 5 m digital surface models (DSMs) to 0.5 m resolution by guiding a denoising diffusion process with high‑resolution spectral images. This approach transfers fine visual details—such as crisp outlines and roof structures—from the imagery into the elevation maps, yielding more accurate surface geometry than traditional interpolation or filtering. Experiments on Central European cities show that the resulting DSMs exhibit improved structural detail and overall quality.
arXiv:2609.31199v1 Announce Type: cross
Abstract: Large-scale Digital Surface Models (DSMs) can be produced cost-effectively from satellite images via stereo-photogrammetry. However, the resulting 3D...
By Antoine Lorentz, St\'ephane May, Valentine Bellet, Dawa Derksen, Bastien Nespoulous
arXiv:2607. 08711v1 Announce Type: cross Abstract: Accurate 3D terrain maps are essential for emergency response when assessing wildfire hazards.
By Xiao Fu, Yue Hu, Meida Chen, Peter Anthony Beerel, Barath Raghavan
Skyfall-GS is a hybrid framework that generates large‑scale, city‑block‑sized 3D urban scenes by combining satellite imagery for coarse geometry with open‑domain diffusion models for detailed appearance. It uses a curriculum‑driven iterative refinement to improve geometric completeness and photorealistic textures, eliminating the need for costly 3D annotations. Experiments show that Skyfall‑GS achieves better cross‑view geometry consistency and more realistic textures than existing methods.
By Jie-Ying Lee, Yi-Ruei Liu, Shr-Ruei Tsai, Wei-Cheng Chang, Chung-Ho Wu, Jiewen Chan, Zhenjun Zhao, Chieh Hubert Lin, Yu-Lun Liu
PhiSat‑2 offers 4.75 m multispectral imagery that can be used for monocular building‑height estimation. The authors created the PhiSat‑2–Height Dataset (PHDataset), comprising 9,475 co‑registered patch pairs from 26 cities, and developed the Two‑Stream Ordinal Network (TSONet) that uses multiscale decoupled height representation and footprint‑conditioned height reconstruction. In city‑disjoint tests, TSONet improves building RMSE and MAE by 3.64 % and 4.49 % over the best existing method, and PhiSat‑2 outperforms Sentinel‑2 and Landsat 8, demonstrating its value for urban height mapping.
By Yanjiao Song, Bowen Cai, Timo Balz, Zhenfeng Shao, Neema Simon Sumari, James Magidi, Walter Musakwa
Accurate 3D terrain maps are essential for emergency response when assessing wildfire hazards. However, wildfire-prone regions often span vast areas where conventional reconstruction methods underperform.
arXiv:2610.27564v1 Announce Type: cross
Abstract: Generating high-fidelity, city-scale 3D environments plays a crucial role in applications such as virtual reality, gaming, and urban digital twins. H...
By Yuchen Zou, Lihuang Fang, Siyu Zhu, Xiao Hu
arXiv:2609.06436v2 Announce Type: replace
Abstract: High-resolution 3D asset generation is vital in various 3D applications. Existing state-of-the-art diffusion-based models remain constrained by fix...
By Yuxin Liu, Minshan Xie, Jiawen Liang, Runsong Zhu, Chi-Wing Fu, Tien-Tsin Wong
arXiv:2607. 05292v1 Announce Type: cross Abstract: Super-resolving coarse atmospheric fields to local PM$_{2.
By Guorun Wang, Simone Foti, Andreas D. Demou, Leonidas Kotoulas, Theodoros Christoudias, Alexandros Koliousis, Mihalis Nicolaou, Stefanos Zafeiriou
arXiv:2608.22821v1 Announce Type: new
Abstract: We present SiZeUp, a fast and scalable approach for constructing large-scale 3D urban proxy models directly from calibrated oblique aerial imagery. Our...
By Wenjun Zhou, Yunshan Li, Qiaoyu Zhu, Weidan Xiong, Hao Zhang, Daniel Cohen-Or, Hui Huang
Generating high-fidelity, city-scale 3D environments plays a crucial role in applications such as virtual reality, gaming, and urban digital twins. However, the scarcity of real-world city-scale 3D tr...
arXiv:2608. 20149v1 Announce Type: new Abstract: This article explores the performance of analytical and neural-based hillshading methods in a dense urban environment using high-resolution digital elevation model (DEM) and digital surface model (DSM) data for downtown Calgary.
By Emmanuel Stefanakis