Publications de Pascal Fua | EPFL Graph Search

Harnessing deep learning to detect bronchiolitis obliterans syndrome from chest CT

Pascal Fua, Michele De Palma, Nahal Mansouri, Jakub Jan Gwizdala

BackgroundBronchiolitis Obliterans Syndrome (BOS), a fibrotic airway disease that may develop after lung transplantation, conventionally relies on pulmonary function tests (PFTs) for diagnosis due to limitations of CT imaging. Deep neural networks (DNNs) h ...

SPRINGERNATURE2025

Deep Active Latent Surfaces for Medical Geometries

Pascal Fua

Shape priors have long been known to be effective when reconstructing 3D shapes from noisy or incomplete data. When using a deep-learning based shape representation, this often involves learning a latent representation, which can be either in the form of a ...

2025

MetaCap: Meta-learning Priors from Multi-view Imagery for Sparse-View Human Performance Capture and Rendering

Pascal Fua

Faithful human performance capture and free-view rendering from sparse RGB observations is a long-standing problem in Vision and Graphics. The main challenges are the lack of observations and the inherent ambiguities of the setting, e.g. occlusions and dep ...

Springer Science and Business Media Deutschland GmbH2025

A Latent Implicit 3D Shape Model for Multiple Levels of Detail

Pascal Fua, Benoît Alain René Guillard

Implicit neural representations map a shape-specific latent code and a 3D coordinate to its corresponding signed distance (SDF) value. However, this approach only offers a single level of detail. Emulating low levels of detail can be achieved with shallow ...

Springer Nature (Switzerland)2025

Automated Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Pascal Fua, Zhen Wei

Traditional aerodynamic shape optimization (ASO) is costly and time-intensive, requiring extensive manual tuning for parameterization to define the design space and manipulate geometries. Conventional parameterization methods limit flexibility and demand s ...

American Institute of Aeronautics and Astronautics (AIAA)2025

Vision-based power line cables and pylons detection for low flying aircraft

Pascal Fua, Soumava Kumar Roy, Jakub Jan Gwizdala, Mian Akbar Shah

Power lines are dangerous for low-flying aircraft, especially in low-visibility conditions. Thus, a vision-based system able to analyze the aircraft's surroundings and to provide the pilots with a "second pair of eyes" can contribute to enhancing their saf ...

SPRINGER2025

A novel immersive catheter ablation simulator based on individualized 3D MR patients' heart models improves ablation performance of future electrophysiologists

Pascal Fua

Oxford University Press (OUP)2025

Temporally-Consistent Surface Reconstruction Using Metrically-Consistent Atlases

Pascal Fua, Mathieu Salzmann, Shaifali Parashar, Jan Bednarík

We propose a method for unsupervised reconstruction of a temporally-consistent sequence of surfaces from a sequence of time-evolving point clouds. It yields dense and semantically meaningful correspondences between frames. We represent the reconstructed su ...

2025

Single View Garment Reconstruction Using Diffusion Mapping Via Pattern Coordinates

Pascal Fua, Ren Li, Corentin Camille Marius Dumery

2025

Real-time Free-view Human Rendering from Sparse-view RGB Videos using Double Unprojected Textures

Pascal Fua

Real-time free-view human rendering from sparse-view RGB inputs is a challenging task due to the sensor scarcity and the tight time budget. To ensure efficiency, recent methods leverage 2D CNNs operating in texture space to learn rendering primitives. Howe ...

IEEE2025

Efficient anatomical labeling of pulmonary tree structures via deep point-graph representation-based implicit fields

Pascal Fua, Jiancheng Yang

Pulmonary diseases rank prominently among the principal causes of death worldwide. Curing them will require, among other things, a better understanding of the complex 3D tree-shaped structures within the pulmonary system, such as airways, arteries, and vei ...

2025

Garment Recovery with Shape and Deformation Priors

Pascal Fua, Benoît Alain René Guillard, Ren Li, Corentin Camille Marius Dumery

While modeling people wearing tight-fitting clothing has made great strides in recent years, loose-fitting clothing remains a challenge. We propose a method that delivers realistic garment models from real-world images, regardless of garment shape or defor ...

2024

CLOAF: CoLlisiOn-Aware Human Flow

Pascal Fua, Martin Pierre Engilberge, Andrey Davydov

Even the best current algorithms for estimating body 3D shape and pose yield results that include body self- intersections. In this paper, we present CLOAF, which exploits the diffeomorphic nature of Ordinary Differential Equations to eliminate such self-i ...

IEEE2024

Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes

Pascal Fua, Mathieu Salzmann, Andrey Davydov

When enough annotated training data is available, supervised deep-learning. algorithms excel at estimating human body pose and shape using a single camera. The effects of too little such data being available can be mitigated by using other information sour ...

2024

DeepMesh: Differentiable Iso-Surface Extraction

Pascal Fua, Timur Bagautdinov, Pierre Bruno Baqué, Edoardo Remelli, Benoît Alain René Guillard, Pierre Mathieu Yvernay

2024

Reconstruction of Manipulated Garment with Guided Deformation Prior

Pascal Fua, Zhantao Deng, Ren Li, Corentin Camille Marius Dumery

Modeling the shape of garments has received much attention, but most existing approaches assume the garments to be worn by someone, which constrains the range of shapes they can assume. In this work, we address shape recovery when garments are being manipu ...

2024

A Closed-Form Pairwise Solution to Local Non-Rigid Structure-from-Motion

Pascal Fua, Mathieu Salzmann, Shaifali Parashar, Yuxuan Long

2024

No Identity, no problem: Motion through detection for people tracking

Pascal Fua, Martin Pierre Engilberge

Tracking-by-detection has become the de facto standard approach to people tracking. To increase robustness, some approaches incorporate re-identification using appearance models and regressing motion offset, which requires costly identity annotations. In t ...

2024

MedShapeNet - a large-scale dataset of 3D medical shapes for computer vision

Pascal Fua, Jiancheng Yang

The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growin ...

2024

Detecting Road Obstacles by Erasing Them

Pascal Fua, Mathieu Salzmann, Krzysztof Maciej Lis, Sina Honari

Vehicles can encounter a myriad of obstacles on the road, and it is impossible to record them all beforehand to train a detector. Instead, we select image patches and inpaint them with the surrounding road texture, which tends to remove obstacles from thos ...

2024