687 citations · 1.1k across the 33 of their papers we have counts for
37 papers
Multimodal Object Detection in Remote Sensing
Abdelbadie Belmouhcine, Jean-Christophe Burnel, Luc Courtrai +2
Object detection in remote sensing is a crucial computer vision task that has seen significant advancements with deep learning techniques. However, most existing works in this area…
Weakly supervised marine animal detection from remote sensing images using vector-quantized variational autoencoder
Minh-Tan Pham, Hugo Gangloff, Sébastien Lefèvre
This paper studies a reconstruction-based approach for weakly-supervised animal detection from aerial images in marine environments. Such an approach leverages an anomaly detection…
A Deep Active Contour Model for Delineating Glacier Calving Fronts
Konrad Heidler, Lichao Mou, Erik Loebel +3
Choosing how to encode a real-world problem as a machine learning task is an important design decision in machine learning. The task of glacier calving front modeling has often bee…
DC3DCD: unsupervised learning for multiclass 3D point cloud change detection
Iris de Gélis, Sébastien Lefèvre, Thomas Corpetti
In a constant evolving world, change detection is of prime importance to keep updated maps. To better sense areas with complex geometry (urban areas in particular), considering 3D…
Deep Unsupervised Learning for 3D ALS Point Cloud Change Detection
Iris de Gélis, Sudipan Saha, Muhammad Shahzad +3
Change detection from traditional \added{2D} optical images has limited capability to model the changes in the height or shape of objects. Change detection using 3D point cloud \ad…
Change detection needs change information: improving deep 3D point cloud change detection
Iris de Gélis, Thomas Corpetti, Sébastien Lefèvre
Change detection is an important task that rapidly identifies modified areas, particularly when multi-temporal data are concerned. In landscapes with a complex geometry (e.g., urba…