5 papers
First Shape, Then Meaning: Efficient Geometry and Semantics Learning for Indoor Reconstruction
Remi Chierchia, Léo Lebrat, David Ahmedt-Aristizabal +3
Neural Surface Reconstruction has become a standard methodology for indoor 3D reconstruction, with Signed Distance Functions (SDFs) proving particularly effective for representing…
In Depth We Trust: Reliable Monocular Depth Supervision for Gaussian Splatting
Wenhui Xiao, Ethan Goan, Rodrigo Santa Cruz +4
Using accurate depth priors in 3D Gaussian Splatting helps mitigate artifacts caused by sparse training data and textureless surfaces. However, acquiring accurate depth maps requir…
NC-Reg : Neural Cortical Maps for Rigid Registration
Ines Vati, Pierrick Bourgeat, Rodrigo Santa Cruz +4
We introduce neural cortical maps, a continuous and compact neural representation for cortical feature maps, as an alternative to traditional discrete structures such as grids and…
Non-Invasive 3D Wound Measurement with RGB-D Imaging
Lena Harkämper, Leo Lebrat, David Ahmedt-Aristizabal +3
Chronic wound monitoring and management require accurate and efficient wound measurement methods. This paper presents a fast, non-invasive 3D wound measurement algorithm based on R…
Multi-View Consistent Wound Segmentation With Neural Fields
Remi Chierchia, Léo Lebrat, David Ahmedt-Aristizabal +4
Wound care is often challenged by the economic and logistical burdens that consistently afflict patients and hospitals worldwide. In recent decades, healthcare professionals have s…