Hello, I'm Ouasfi Amine

I am a PhD Student at INRIA in France, working with Prof. Adnane Boukhayma and Prof. Eric Marchand.
My research interests focus on 3D computer vision, generative models, and computer graphics. Previously, I worked on improving generalizable implicit reconstuction models. I’m currently exploring implicit representation learning from sparse inputs (pointclouds, multi-view images).


Publications

SparseCraft: Few-Shot Neural Reconstruction through Stereopsis Guided Geometric Linearization

SparseCraft: Few-Shot Neural Reconstruction through Stereopsis Guided Geometric Linearization

Mae Younes*, Amine Ouasfi*, Adnane Boukhayma
ECCV, 2024

Imporving Novel-View Synthesis and reconstruction from sparse views without data priors through local Geometric Linearization.

Unsupervised Occupancy Learning from Sparse Point Cloud

Unsupervised Occupancy Learning from Sparse Point Cloud

Amine Ouasfi, Adnane Boukhayma
CVPR, 2024 Highlight

Local linearization and Minimal entropy fields regularization for occupancy learning from sparse point cloud without ground-truth supervision.

Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries

Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries

Amine Ouasfi, Adnane Boukhayma
ICML, 2024

Adversarial regularization for SDF optimization from sparse point cloud without ground-truth supervision.

Mixing-denoising generalizable occupancy networks

Mixing-denoising generalizable occupancy networks

Amine Ouasfi, Adnane Boukhayma
3DV, 2024

Making generalizable implicit representations robust to the input noise and sparsity by relaxing the inductive biais of convolutions with MLP-based local encoding.

Robustifying Generalizable Implicit Shape Networks with a Tunable Non-Parametric Model

Robustifying Generalizable Implicit Shape Networks with a Tunable Non-Parametric Model

Amine Ouasfi, Adnane Boukhayma
NeurIPS, 2024

Leveraging kernel methods for Fast test-time adaptation of pretrained networks with a shape specific trade-of between expressiveness and regularization.

Few ‘Zero Level Set’-Shot Learning of Shape Signed Distance Functions in Feature Space

Few ‘Zero Level Set’-Shot Learning of Shape Signed Distance Functions in Feature Space

Amine Ouasfi, Adnane Boukhayma
ECCV, 2022

Conditioning implicit representations on sparse inputs through meta-leanring in feature space.