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…
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…
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…
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…