41 citations · 71 across the 6 of their papers we have counts for
11 papers · 1 filter
Learning Graph Regularisation for Guided Super-Resolution
Riccardo de Lutio, Alexander Becker, Stefano D'Aronco +3
We introduce a novel formulation for guided super-resolution. Its core is a differentiable optimisation layer that operates on a learned affinity graph. The learned graph potential…
Digital Taxonomist: Identifying Plant Species in Community Scientists' Photographs
Riccardo de Lutio, Yihang She, Stefano D'Aronco +4
Automatic identification of plant specimens from amateur photographs could improve species range maps, thus supporting ecosystems research as well as conservation efforts. However,…
Mapping oil palm density at country scale: An active learning approach
Andrés C. Rodríguez, Stefano D'Aronco, Konrad Schindler +1
Accurate mapping of oil palm is important for understanding its past and future impact on the environment. We propose to map and count oil palms by estimating tree densities per pi…
PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds
Yujia Liu, Stefano D'Aronco, Konrad Schindler +1
We introduce PC2WF, the first end-to-end trainable deep network architecture to convert a 3D point cloud into a wireframe model. The network takes as input an unordered set of 3D p…
Crop mapping from image time series: deep learning with multi-scale label hierarchies
Mehmet Ozgur Turkoglu, Stefano D'Aronco, Gregor Perich +4
The aim of this paper is to map agricultural crops by classifying satellite image time series. Domain experts in agriculture work with crop type labels that are organised in a hier…
Crop Classification under Varying Cloud Cover with Neural Ordinary Differential Equations
Nando Metzger, Mehmet Ozgur Turkoglu, Stefano D'Aronco +2
Optical satellite sensors cannot see the Earth's surface through clouds. Despite the periodic revisit cycle, image sequences acquired by Earth observation satellites are therefore…