activity
20182026
most citedBuilding Instance Classification Using Street View Images

373 citations · 1.4k across the 19 of their papers we have counts for

collaborators

22 papers

cs.CV2026

deSEO: Physics-Aware Dataset Creation for High-Resolution Satellite Image Shadow Removal

Lorenzo Beltrame, Jules Salzinger, Filip Svoboda +4

Shadows cast by terrain and tall structures remain a major obstacle for high-resolution satellite image analysis, degrading classification, detection, and 3D reconstruction perform…

cs.CV2026

Winner of CVPR2026 NTIRE Challenge on Image Shadow Removal: Semantic and Geometric Guidance for Shadow Removal via Cascaded Refinement

Lorenzo Beltrame, Jules Salzinger, Filip Svoboda +4

We present a three-stage progressive shadow-removal pipeline for the CVPR2026 NTIRE WSRD+ challenge. Built on OmniSR, our method treats deshadowing as iterative direct refinement,…

cs.LG2023★ 2 cited

Harnessing Administrative Data Inventories to Create a Reliable Transnational Reference Database for Crop Type Monitoring

Maja Schneider, Marco Körner

With leaps in machine learning techniques and their applicationon Earth observation challenges has unlocked unprecedented performance across the domain. While the further developme…

cs.OH2023

EuroCrops: All you need to know about the Largest Harmonised Open Crop Dataset Across the European Union

Maja Schneider, Tobias Schelte, Felix Schmitz +1

EuroCrops contains geo-referenced polygons of agricultural croplands from 16 countries of the European Union (EU) as well as information on the respective crop species grown there.…

cs.DL2022★ 3 cited

Challenges and Opportunities of Large Transnational Datasets: A Case Study on European Administrative Crop Data

Maja Schneider, Christian Marchington, Marco Körner

Expansive, informative datasets are vital in providing foundations and possibilities for scientific research and development across many fields of study. Assembly of grand datasets…

eess.IV2021★ 2 cited

EuroCrops: A Pan-European Dataset for Time Series Crop Type Classification

Maja Schneider, Amelie Broszeit, Marco Körner

We present EuroCrops, a dataset based on self-declared field annotations for training and evaluating methods for crop type classification and mapping, together with its process of…