2 citations · 3 across the 11 of their papers we have counts for
12 papers
PartiCam: Camera Controlled Video Generation with Reward Guidance
Amine Ouasfi, Runjia Li, Junlin Han +3
We present PartiCam, a training-free Particle filtering rooted method for improved Camera controlled video generation. Generating videos that follow a precisely specified camera tr…
MUKA: Multi Kernel Audio Adaptation Of Audio-Language Models
Reda Bensaid, Amine Ouasfi, Yassir Bendou +4
Multimodal foundation models have demonstrated impressive generalization capabilities, yet efficiently adapting them to new tasks in a few-shot setting remains a critical challenge…
RibPull: Implicit Occupancy Fields and Medial Axis Extraction for CT Ribcage Scans
Emmanouil Nikolakakis, Amine Ouasfi, Julie Digne +1
We present RibPull, a methodology that utilizes implicit occupancy fields to bridge computational geometry and medical imaging. Implicit 3D representations use continuous functions…
Sparfels: Fast Reconstruction from Sparse Unposed Imagery
Shubhendu Jena, Amine Ouasfi, Mae Younes +1
We present a method for Sparse view reconstruction with surface element splatting that runs within 3 minutes on a consumer grade GPU. While few methods address sparse radiance fiel…
ProKeR: A Kernel Perspective on Few-Shot Adaptation of Large Vision-Language Models
Yassir Bendou, Amine Ouasfi, Vincent Gripon +1
The growing popularity of Contrastive Language-Image Pretraining (CLIP) has led to its widespread application in various visual downstream tasks. To enhance CLIP's effectiveness an…
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…
Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
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.…
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.…
Robustifying Generalizable Implicit Shape Networks with a Tunable Non-Parametric Model
Amine Ouasfi, Adnane Boukhayma
Feedforward generalizable models for implicit shape reconstruction from unoriented point cloud present multiple advantages, including high performance and inference speed. However,…
Mixing-Denoising Generalizable Occupancy Networks
Amine Ouasfi, Adnane Boukhayma
While current state-of-the-art generalizable implicit neural shape models rely on the inductive bias of convolutions, it is still not entirely clear how properties emerging from su…
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…