11 citations · 29 across the 25 of their papers we have counts for
30 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…
3DSS: 3D Surface Splatting for Inverse Rendering
Mae Younes, Adnane Boukhayma
We present 3D Surface Splatting (3DSS), the first differentiable surface splatting renderer for physically-based inverse rendering from multi-view images. Our central insight is th…
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…
GTAvatar: Bridging Gaussian Splatting and Texture Mapping for Relightable and Editable Gaussian Avatars
Kelian Baert, Mae Younes, Francois Bourel +2
Recent advancements in Gaussian Splatting have enabled increasingly accurate reconstruction of photorealistic head avatars, opening the door to numerous applications in visual effe…
TextureSplat: Per-Primitive Texture Mapping for Reflective Gaussian Splatting
Mae Younes, Adnane Boukhayma
Gaussian Splatting have demonstrated remarkable novel view synthesis performance at high rendering frame rates. Optimization-based inverse rendering within complex capture scenario…
Anti-Aliased 2D Gaussian Splatting
Mae Younes, Adnane Boukhayma
2D Gaussian Splatting (2DGS) has recently emerged as a promising method for novel view synthesis and surface reconstruction, offering better view-consistency and geometric accuracy…
SparSplat: Fast Multi-View Reconstruction with Generalizable 2D Gaussian Splatting
Shubhendu Jena, Shishir Reddy Vutukur, Adnane Boukhayma
Recovering 3D information from scenes via multi-view stereo reconstruction (MVS) and novel view synthesis (NVS) is inherently challenging, particularly in scenarios involving spars…
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…
D-Garment: Physically Grounded Latent Diffusion for Dynamic Garment Deformations
Antoine Dumoulin, Adnane Boukhayma, Laurence Boissieux +3
We present a method to dynamically deform 3D garments, in the form of a 3D polygon mesh, based on body shape, motion, and physical cloth material properties. Considering physical c…
Few-Shot Multi-Human Neural Rendering Using Geometry Constraints
Qian li, Victoria Fernàndez Abrevaya, Franck Multon +1
We present a method for recovering the shape and radiance of a scene consisting of multiple people given solely a few images. Multi-human scenes are complex due to additional occlu…
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…
GeoTransfer : Generalizable Few-Shot Multi-View Reconstruction via Transfer Learning
Shubhendu Jena, Franck Multon, Adnane Boukhayma
This paper presents a novel approach for sparse 3D reconstruction by leveraging the expressive power of Neural Radiance Fields (NeRFs) and fast transfer of their features to learn…
SPARK: Self-supervised Personalized Real-time Monocular Face Capture
Kelian Baert, Shrisha Bharadwaj, Fabien Castan +4
Feedforward monocular face capture methods seek to reconstruct posed faces from a single image of a person. Current state of the art approaches have the ability to regress parametr…
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…
Neural Mesh-Based Graphics
Shubhendu Jena, Franck Multon, Adnane Boukhayma
We revisit NPBG, the popular approach to novel view synthesis that introduced the ubiquitous point feature neural rendering paradigm. We are interested in particular in data-effici…
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…
Monocular Human Shape and Pose with Dense Mesh-borne Local Image Features
Shubhendu Jena, Franck Multon, Adnane Boukhayma
We propose to improve on graph convolution based approaches for human shape and pose estimation from monocular input, using pixel-aligned local image features. Given a single input…
Neural Human Deformation Transfer
Jean Basset, Adnane Boukhayma, Stefanie Wuhrer +2
We consider the problem of human deformation transfer, where the goal is to retarget poses between different characters. Traditional methods that tackle this problem require a clea…