1 citations · 1 across the 2 of their papers we have counts for
3 papers
GEKey: Learning Geodesic Eccentric 3D Keypoints via Self-Supervision
Pierre Onghena, Santiago Velasco-Forero, Beatriz Marcotegui
Point clouds represent 3D object geometry as sets of spatial coordinates. A fundamental task in their analysis is keypoint detection, i.e., identifying a sparse subset of points th…
LmPT: Conditional Point Transformer for Anatomical Landmark Detection on 3D Point Clouds
Matteo Bastico, Pierre Onghena, David Ryckelynck +5
Accurate identification of anatomical landmarks is crucial for various medical applications. Traditional manual landmarking is time-consuming and prone to inter-observer variabilit…
MorphoSkel3D: Morphological Skeletonization of 3D Point Clouds for Informed Sampling in Object Classification and Retrieval
Pierre Onghena, Santiago Velasco-Forero, Beatriz Marcotegui
Point clouds are a set of data points in space to represent the 3D geometry of objects. A fundamental step in the processing is to identify a subset of points to represent the shap…