119 citations · 124 across the 8 of their papers we have counts for
10 papers
Toward a foundation model for forest point clouds
Yuanwen Yue, Stefano Puliti, Damien Robert +7
Forest inventories increasingly rely on artificial intelligence (AI) models to derive forest attributes from large-scale 3D point clouds. Current models are typically specialized t…
Quantifying the Uncertainty of Foundation Models with Singular Value Ensembles
Mehmet Ozgur Turkoglu, Dominik J. Mühlematter, Alexander Becker +2
Foundation models have become a dominant paradigm in machine learning, achieving remarkable performance across diverse tasks through large-scale pretraining. However, they often yi…
FireScope: Wildfire Risk Raster Prediction with a Chain-of-Thought Oracle
Mario Markov, Stefan Maria Ailuro, Luc Van Gool +2
Predicting wildfire risk is a reasoning-intensive spatial problem that requires the integration of visual, climatic, and geographic factors to infer continuous risk maps. Existing…
Beyond Pretty Pictures: Combined Single- and Multi-Image Super-resolution for Sentinel-2 Images
Aditya Retnanto, Son Le, Sebastian Mueller +4
Super-resolution aims to increase the resolution of satellite images by reconstructing high-frequency details, which go beyond naïve upsampling. This has particular relevance for E…
Cutting-edge 3D reconstruction solutions for underwater coral reef images: A review and comparison
Jiageng Zhong, Ming Li, Armin Gruen +3
Corals serve as the foundational habitat-building organisms within reef ecosystems, constructing extensive structures that extend over vast distances. However, their inherent fragi…
Uncertainties of Satellite-based Essential Climate Variables from Deep Learning
Junyang Gou, Arnt-Børre Salberg, Mostafa Kiani Shahvandi +9
Accurate uncertainty information associated with essential climate variables (ECVs) is crucial for reliable climate modeling and understanding the spatiotemporal evolution of the E…
GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generation
Dingdong Yang, Yizhi Wang, Konrad Schindler +2
We propose GALA, a novel representation of 3D shapes that (i) excels at capturing and reproducing complex geometry and surface details, (ii) is computationally efficient, and (iii)…
Is Continual Learning Ready for Real-world Challenges?
Theodora Kontogianni, Yuanwen Yue, Siyu Tang +1
Despite continual learning's long and well-established academic history, its application in real-world scenarios remains rather limited. This paper contends that this gap is attrib…
SegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data
Maciej Wielgosz, Stefano Puliti, Binbin Xiang +2
This research advances individual tree crown (ITC) segmentation in lidar data, using a deep learning model applicable to various laser scanning types: airborne (ULS), terrestrial (…
Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning
Binbin Xiang, Maciej Wielgosz, Theodora Kontogianni +4
Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services. Modern airborne laser scanners deliver…