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Pascal Fua

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Related publications (322)

Structured Prediction of 3D Human Pose with Deep Neural Networks

Pascal Fua, Mathieu Salzmann, Vincent Lepetit, Bugra Tekin, Isinsu Katircioglu

Most recent approaches to monocular 3D pose estimation rely on Deep Learning. They either train a Convolutional Neural Network to directly regress from image to 3D pose, which ignores the dependencies between human joints, or model these dependencies via a ...

2016

Direct Prediction of 3D Body Poses from Motion Compensated Sequences

Pascal Fua, Vincent Lepetit, Bugra Tekin, Artem Rozantsev

We propose an efficient approach to exploiting motion information from consecutive frames of a video sequence to recover the 3D pose of people. Previous approaches typically compute candidate poses in individual frames and then link them in a post-processi ...

2016

What Players do with the Ball: A Physically Constrained Interaction Modeling

Pascal Fua, Xinchao Wang, Andrii Maksai

Tracking the ball is critical for video-based analysis of team sports. However, it is difficult, especially in low resolution images, due to the small size of the ball, its speed that creates motion blur, and its often being occluded by players. In this pa ...

2016

Parsing human skeletons in an operating room

Pascal Fua, Slobodan Ilic, Horesh Beny Ben Shitrit, Vasileios Belagiannis, Xinchao Wang

Multiple human pose estimation is an important yet challenging problem. In an Operating Room (OR) environment, the 3D body poses of surgeons and medical staff can provide important clues for surgical workflow analysis. For that purpose, we propose an algor ...

Springer Verlag2016

Learning to Assign Orientations to Feature Points

Pascal Fua, Vincent Lepetit, Yannick Verdie, Kwang Moo Yi

We show how to train a Convolutional Neural Network to assign a canonical orientation to feature points given an image patch centered on the feature point. Our method improves feature point matching upon the state-of-the art and can be used in conjunction ...

2016

Vision-Based Unmanned Aerial Vehicle Detection and Tracking for Sense and Avoid Systems

Denis Gillet, Alcherio Martinoli, Pascal Fua, Vincent Lepetit, Steven Adriaan Roelofsen, Artem Rozantsev, Krishna Raj Sapkota

We propose an approach for on-line detection of small Unmanned Aerial Vehicles (UAVs) and estimation of their relative positions and velocities in the 3D environment from a single moving camera in the context of sense and avoid systems. This problem is cha ...

Ieee2016

Multiscale Centerline Detection

Pascal Fua, Vincent Lepetit, Engin Türetken, Amos Sironi

Finding the centerline and estimating the radius of linear structures is a critical first step in many applications, ranging from road delineation in 2D aerial images to modeling blood vessels, lung bronchi, and dendritic arbors in 3D biomedical image stac ...

Institute of Electrical and Electronics Engineers2016

Principled Parallel Mean-Field Inference for Discrete Random Fields

Pascal Fua, François Fleuret, Timur Bagautdinov, Pierre Bruno Baqué

Mean-field variational inference is one of the most popular approaches to inference in discrete random fields. Standard mean-field optimization is based on coordinate descent and in many situations can be impractical. Thus, in practice, various parallel te ...

2016

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

Template-based Monocular 3D Shape Recovery using Laplacian Meshes

Pascal Fua, Jonas Olof Martin Östlund, Tien Dat Ngo

We show that by extending the Laplacian formalism, which was first introduced in the Graphics community to regularize 3D meshes, we can turn the monocular 3D shape reconstruction of a deformable surface given correspondences with a reference image into a w ...

Institute of Electrical and Electronics Engineers2016

Active Learning for Delineation of Curvilinear Structures

Pascal Fua, Raphael Sznitman, Przemyslaw Rafal Glowacki, Agata Justyna Mosinska

2016

Measuring the accuracy of softball impact simulations

Pascal Fua

A study has been conducted to review viscoelastic and foam-constitutive models to describe sport ball response to impact with a rigid cylindrical surface. The impact model was developed to simulate a ball-bat collision. Comparisons were made to actual impa ...

Springer London Ltd2016

Simultaneous segmentation and anatomical labeling of the cerebral vasculature

Pascal Fua, David Robben

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

Learning to Match Aerial Images with Deep Attentive Architectures

Pascal Fua, Eduard Trulls Fortuny, Hani Altwaijry

Image matching is a fundamental problem in Computer Vision. In the context of feature-based matching, SIFT and its variants have long excelled in a wide array of applications. However, for ultra-wide baselines, as in the case of aerial images captured unde ...

2016

On Rendering Synthetic Images for Training an Object Detector

Pascal Fua, Vincent Lepetit, Artem Rozantsev

We propose a novel approach to synthesizing images that are effective for training object detectors. Starting from a small set of real images, our algorithm estimates the rendering parameters required to synthesize similar images given a coarse 3D model of ...

Elsevier2015

Domain Adaptation for Microscopy Imaging

Pascal Fua, Christos Marios Christoudias, Carlos Joaquin Becker

Electron and Light Microscopy imaging can now deliver high-quality image stacks of neural structures. However, the amount of human annotation effort required to analyze them remains a major bottleneck. While Machine Learning algorithms can be used to help ...

Institute of Electrical and Electronics Engineers2015

Non-Rigid Graph Registration using Active Testing Search

Pascal Fua, Jan Kybic, Raphael Sznitman, Miguel Amável Dos Santos Pinheiro

We present a new approach for matching sets of branching curvilinear structures that form graphs embedded in R2 or R3 and may be subject to deformations. Unlike earlier methods, ours does not rely on local appearance similarity nor does require a good init ...

Institute of Electrical and Electronics Engineers2015

Probability Occupancy Maps for Occluded Depth Images

Pascal Fua, François Fleuret, Timur Bagautdinov

2015

Learning Structured Models for Segmentation of 2D and 3D Imagery

Pascal Fua, Graham Knott, Kevin Smith, Aurélien Lucchi, Yunpeng Li, Carlos Joaquin Becker, Pablo Marquez Neila

Efficient and accurate segmentation of cellular structures in microscopic data is an essential task in medical imaging. Many state-of-the-art approaches to image segmentation use structured models whose parameters must be carefully chosen for optimal perfo ...

Institute of Electrical and Electronics Engineers2015

Learning Separable Filters

Pascal Fua, Vincent Lepetit, Roberto Rigamonti, Bugra Tekin, Amos Sironi

Learning filters to produce sparse image representations in terms of overcomplete dictionaries has emerged as a powerful way to create image features for many different purposes. Unfortunately, these filters are usually both numerous and non-separable, mak ...

Ieee Computer Soc2015

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