5 papers
High Resolution UDF Meshing via Iterative Networks
Federico Stella, Nicolas Talabot, Hieu Le +1
Unsigned Distance Fields (UDFs) are a natural implicit representation for open surfaces but, unlike Signed Distance Fields (SDFs), are challenging to triangulate into explicit mesh…
High-Fidelity and Generalizable Neural Surface Reconstruction with Sparse Feature Volumes
Aoxiang Fan, Corentin Dumery, Nicolas Talabot +2
Generalizable neural surface reconstruction has become a compelling technique to reconstruct from few images without per-scene optimization, where dense 3D feature volume has prove…
A View-consistent Sampling Method for Regularized Training of Neural Radiance Fields
Aoxiang Fan, Corentin Dumery, Nicolas Talabot +1
Neural Radiance Fields (NeRF) has emerged as a compelling framework for scene representation and 3D recovery. To improve its performance on real-world data, depth regularizations h…
PartSDF: Part-Based Implicit Neural Representation for Composite 3D Shape Parametrization and Optimization
Nicolas Talabot, Olivier Clerc, Arda Cinar Demirtas +4
Accurate 3D shape representation is essential in engineering applications such as design, optimization, and simulation. In practice, engineering workflows require structured, part-…
Counting Stacked Objects
Corentin Dumery, Noa Etté, Aoxiang Fan +4
Visual object counting is a fundamental computer vision task underpinning numerous real-world applications, from cell counting in biomedicine to traffic and wildlife monitoring. Ho…