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Pascal Fua

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Publications associées (319)

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Simultaneous segmentation and anatomical labeling of the cerebral vasculature

Pascal Fua

We present a novel algorithm for the simultaneous segmentation and anatomical labeling of the cerebral vasculature. Unlike existing approaches that first attempt to obtain a good segmentation and then perform labeling, we optimize for both by simultaneousl ...

Elsevier2016

Multi-Commodity Network Flow for Tracking Multiple People

Pascal Fua, François Fleuret, Horesh Beny Ben Shitrit

In this paper, we show that tracking multiple people whose paths may intersect can be formulated as a multi-commodity network flow problem. Our proposed framework is designed to exploit image appearance cues to prevent identity switches. Our method is effe ...

Institute of Electrical and Electronics Engineers2014

A Real-Time Deformable Detector

Pascal Fua, François Fleuret, David Hasler, Karim Ali

We propose a new learning strategy for object detection. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform base ...

Institute of Electrical and Electronics Engineers2012

ActiveMoCap: Optimized Viewpoint Selection for Active Human Motion Capture

Pascal Fua, Mathieu Salzmann, Helge Jochen Rhodin, Sena Kiciroglu

The accuracy of monocular 3D human pose estimation depends on the viewpoint from which the image is captured. While freely moving cameras, such as on drones, provide control over this viewpoint, automatically positioning them at the location which will yie ...

IEEE2020

Appearance-based Keypoint Clustering

Pascal Fua, Sabine Süsstrunk, Vincent Lepetit

We present an algorithm for clustering sets of detected interest points into groups that correspond to visually distinct structure. Through the use of a suitable colour and texture representation, our clustering method is able to identify keypoints that be ...

2009

Motion Prediction Using Temporal Inception Module

Pascal Fua, Mathieu Salzmann, Wei Wang, Sena Kiciroglu

Human motion prediction is a necessary component for many applications in robotics and autonomous driving. Recent methods propose using sequence-to-sequence deep learning models to tackle this problem. However, they do not focus on exploiting different tem ...

Springer, Cham2020

Boosting Binary Keypoint Descriptors

Pascal Fua, Vincent Lepetit, Tomasz Piotr Trzcinski, Christos Marios Christoudias

Binary keypoint descriptors provide an efficient alternative to their floating-point competitors as they enable faster processing while requiring less memory. In this paper, we propose a novel framework to learn an extremely compact binary descriptor we ca ...

2013

Observable Subspaces for 3D Human Motion Recovery

Pascal Fua, Mathieu Salzmann

The articulated body models used to represent human motion typically have many degrees of freedom, usually expressed as joint angles that are highly correlated. The true range of motion can therefore be represented by latent variables that span a low-dimen ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization

Edouard Robert Albert Patrick Dufour, Colin Pelletier, Pascal Fua, Zhen Wei

Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...

2024

Geodesic Convolutional Neural Network Characterization of Macro-Porous Latent Thermal Energy Storage

Pascal Fua, Sophia Haussener, Pierre Bruno Baqué, Nithin Mallya, Pierre Mathieu Yvernay

High-temperature latent heat thermal energy storage with metallic alloy phase change materials (PCMs) utilize the high latent heat and high thermal conductivity to gain a competitive edge over existing sensible and latent storage technologies. Novel macrop ...

2023

Pose Estimation for Category Specific Multiview Object Localization

Pascal Fua, Vincent Lepetit, Mustafa Özuysal

We propose an approach to overcome the two main challenges of 3D multiview object detection and localization: The variation of object features due to changes in the viewpoint and the variation in the size and aspect ratio of the object. Our approach procee ...

IEEE2009

TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation

Pascal Fua, Mateusz Kozinski, Leonardo Citraro, Subeesh Vasu

Most state-of-the-art approaches to road extraction from aerial images rely on a CNN trained to label road pixels as foreground and remainder of the image as background. The CNN is usually trained by minimizing pixel-wise losses, which is less than ideal t ...

2020

Scalable Unsupervised Domain Adaptation for Electron Microscopy

Pascal Fua, Mathieu Salzmann, Carlos Joaquin Becker, Róger Bermúdez Chacón

While Machine Learning algorithms are key to automating organelle segmentation in large EM stacks, they require annotated data, which is hard to come by in sufficient quantities. Furthermore, images acquired from one part of the brain are not always repres ...

2016

WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection

Pascal Fua, François Fleuret, Tatjana Chavdarova, Andrii Maksai, Cijo Jose

People detection methods are highly sensitive to occlusions between pedestrians, which are extremely frequent in many situations where cameras have to be mounted at a limited height. The reduction of camera prices allows for the generalization of static mu ...

IEEE2018

Multi-Camera People Tracking with a Probabilistic Occupancy Map

Pascal Fua, François Fleuret

Given two to four synchronized video streams taken at eye level and from different angles, we show that we can effectively combine a generative model with dynamic programming to accurately follow up to six individuals across thousands of frames in spite of ...

Institute of Electrical and Electronics Engineers2008

Geometric Graph Matching Using Monte Carlo Tree Search

Pascal Fua, Jan Kybic

We present an efficient matching method for generalized geometric graphs. Such graphs consist of vertices in space connected by curves and can represent many real world structures such as road networks in remote sensing, or vessel networks in medical imagi ...

Ieee Computer Soc2017

Multi-Modal Mean-Fields via Cardinality-Based Clamping

François Fleuret, Pascal Fua

Mean Field inference is central to statistical physics. It has attracted much interest in the Computer Vision community to efficiently solve problems expressible in terms of large Conditional Random Fields. However, since it models the posterior probabilit ...

Ieee2017

Temporal Representation Learning on Monocular Videos for 3D Human Pose Estimation

Pascal Fua, Mathieu Salzmann, Helge Jochen Rhodin, Sina Honari, Victor Constantin

In this paper we propose an unsupervised feature extraction method to capture temporal information on monocular videos, where we detect and encode subject of interest in each frame and leverage contrastive self-supervised (CSS) learning to extract rich lat ...

2022

LIFT: Learned Invariant Feature Transform

Pascal Fua, Vincent Lepetit, Kwang Moo Yi, Eduard Trulls Fortuny

We introduce a novel Deep Network architecture that implements the full feature point handling pipeline, that is, detection, orientation estimation, and feature description. While previous works have successfully tackled each one of these problems individu ...

Springer Int Publishing Ag2016

Robust Multi-View Change Detection

Pascal Fua, François Fleuret

We present a multi-view change detection approach aimed at being robust with respect to common “disturbance factors” yielding image changes in realworld applications. Disturbance factors causing “slow” or “fast-and-global” image variations, such as light c ...

2007