41 citations · 71 across the 6 of their papers we have counts for
12 papers
A Deep Learning Approach for Digital Color Reconstruction of Lenticular Films
Stefano D'Aronco, Giorgio Trumpy, David Pfluger +1
We propose the first accurate digitization and color reconstruction process for historical lenticular film that is robust to artifacts. Lenticular films emerged in the 1920s and we…
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…