22 citations · 32 across the 11 of their papers we have counts for
12 papers
SALVE: A 3D Reconstruction Benchmark of Wounds from Consumer-grade Videos
Remi Chierchia, Leo Lebrat, David Ahmedt-Aristizabal +3
Managing chronic wounds is a global challenge that can be alleviated by the adoption of automatic systems for clinical wound assessment from consumer-grade videos. While 2D image a…
NeRF Director: Revisiting View Selection in Neural Volume Rendering
Wenhui Xiao, Rodrigo Santa Cruz, David Ahmedt-Aristizabal +3
Neural Rendering representations have significantly contributed to the field of 3D computer vision. Given their potential, considerable efforts have been invested to improve their…
Syn3DWound: A Synthetic Dataset for 3D Wound Bed Analysis
Léo Lebrat, Rodrigo Santa Cruz, Remi Chierchia +12
Wound management poses a significant challenge, particularly for bedridden patients and the elderly. Accurate diagnostic and healing monitoring can significantly benefit from moder…
CorticalFlow: Boosting Cortical Surface Reconstruction Accuracy, Regularity, and Interoperability
Rodrigo Santa Cruz, Léo Lebrat, Darren Fu +4
The problem of Cortical Surface Reconstruction from magnetic resonance imaging has been traditionally addressed using lengthy pipelines of image processing techniques like FreeSurf…
CorticalFlow: A Diffeomorphic Mesh Deformation Module for Cortical Surface Reconstruction
Léo Lebrat, Rodrigo Santa Cruz, Frédéric de Gournay +5
In this paper we introduce CorticalFlow, a new geometric deep-learning model that, given a 3-dimensional image, learns to deform a reference template towards a targeted object. To…
MongeNet: Efficient Sampler for Geometric Deep Learning
Léo Lebrat, Rodrigo Santa Cruz, Clinton Fookes +1
Recent advances in geometric deep-learning introduce complex computational challenges for evaluating the distance between meshes. From a mesh model, point clouds are necessary alon…
DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction
Rodrigo Santa Cruz, Leo Lebrat, Pierrick Bourgeat +3
The study of neurodegenerative diseases relies on the reconstruction and analysis of the brain cortex from magnetic resonance imaging (MRI). Traditional frameworks for this task li…
Going deeper with brain morphometry using neural networks
Rodrigo Santa Cruz, Léo Lebrat, Pierrick Bourgeat +5
Brain morphometry from magnetic resonance imaging (MRI) is a consolidated biomarker for many neurodegenerative diseases. Recent advances in this domain indicate that deep convoluti…
Approximation of curves with piecewise constant or piecewise linear functions
Frédéric de Gournay, Jonas Kahn, Léo Lebrat
In this paper we compute the Hausdorff distance between sets of continuous curves and sets of piecewise constant or linear discretizations. These sets are Sobolev balls given by th…
3/4-discrete optimal transport
Frédéric de Gournay, Jonas Kahn, Léo Lebrat
This paper deals with the 3/4-discrete 2-Wasserstein optimal transport between two measures, where one is supported by a set of segment and the other one is supported by a set of D…
Optimal Transport Approximation of 2-Dimensional Measures
Frédéric de Gournay, Jonas Kahn, Léo Lebrat +1
We propose a fast and scalable algorithm to project a given density on a set of structured measures defined over a compact 2D domain. The measures can be discrete or supported on c…
Differentiation and regularity of semi-discrete optimal transport with respect to the parameters of the discrete measure
Frédéric de Gournay, Jonas Kahn, Léo Lebrat
This paper aims at determining under which conditions the semi-discrete optimal transport is twice differentiable with respect to the parameters of the discrete measure and exhibit…