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…
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…
Neural Radiance Fields for the Real World: A Survey
Wenhui Xiao, Remi Chierchia, Rodrigo Santa Cruz +5
Neural Radiance Fields (NeRFs) have remodeled 3D scene representation since release. NeRFs can effectively reconstruct complex 3D scenes from 2D images, advancing different fields…
Wound3DAssist: A Practical Framework for 3D Wound Assessment
Remi Chierchia, Rodrigo Santa Cruz, Léo Lebrat +7
Managing chronic wounds remains a major healthcare challenge, with clinical assessment often relying on subjective and time-consuming manual documentation methods. Although 2D digi…
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…