5 papers · 1 filter
Toward Robust Neural Reconstruction from Sparse Point Sets
Amine Ouasfi, Shubhendu Jena, Eric Marchand +1
We consider the challenging problem of learning Signed Distance Functions (SDF) from sparse and noisy 3D point clouds. In contrast to recent methods that depend on smoothness prior…
SparseCraft: Few-Shot Neural Reconstruction through Stereopsis Guided Geometric Linearization
Mae Younes, Amine Ouasfi, Adnane Boukhayma
We present a novel approach for recovering 3D shape and view dependent appearance from a few colored images, enabling efficient 3D reconstruction and novel view synthesis. Our meth…
Unsupervised Occupancy Learning from Sparse Point Cloud
Amine Ouasfi, Adnane Boukhayma
Implicit Neural Representations have gained prominence as a powerful framework for capturing complex data modalities, encompassing a wide range from 3D shapes to images and audio.…
Learning Generalizable Light Field Networks from Few Images
Qian Li, Franck Multon, Adnane Boukhayma
We explore a new strategy for few-shot novel view synthesis based on a neural light field representation. Given a target camera pose, an implicit neural network maps each ray to it…
Few 'Zero Level Set'-Shot Learning of Shape Signed Distance Functions in Feature Space
Amine Ouasfi, Adnane Boukhayma
We explore a new idea for learning based shape reconstruction from a point cloud, based on the recently popularized implicit neural shape representations. We cast the problem as a…