29 citations · 64 across the 7 of their papers we have counts for
3 papers · 1 filter
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…