Publications de Pascal Fua | EPFL Graph Search

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Estimating a camera pose given a set of 3D-object and 2D-image feature points is a well understood problem when correspondences are given. However, when such correspondences cannot be established a priori, one must simultaneously compute them along with th ...

Dense disparity maps can be computed from wide-baseline stereo pairs but will inevitably contain large areas where the depth cannot be estimated accurately because the pixels are seen in one view only. A traditional approach to this problem is to introduce ...

It is useful to have a small set of representative images from a database of thousands of images to summarize its content. There are two key aspects of such image summaries: how to generate them and how to present them. We address both issues. We extend th ...

We present a method for real-time 3D object instance detection that does not require a time-consuming training stage, and can handle untextured objects. At its core, our approach is a novel image representation for template matching designed to be robust t ...

We demonstrate how to exploit reflections for accurate registration of shiny objects: The lighting environment can be retrieved from the reflections under a distant illumination assumption. Since it remains unchanged when the camera or the object of intere ...

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 ...

Many state-of-the-art delineation methods rely on supervised machine learning algorithms. As a result, they require manually annotated training data, which is tedious to obtain. Furthermore, even minor classification errors may significantly affect the top ...

We present a closed-form solution to the problem of re- covering the 3D shape of a non-rigid potentially stretchable surface from 3D-to-2D correspondences. In other words, we can reconstruct a surface from a single image without a priori knowledge of its d ...

The most recent trend in estimating the 6D pose of rigid objects has been to train deep networks to either directly regress the pose from the image or to predict the 2D locations of 3D keypoints, from which the pose can be obtained using a PnP algorithm. I ...

Long term human motion prediction is essential in safety-critical applications such as human-robot interaction and autonomous driving. In this paper we show that to achieve long term forecasting, predicting human pose at every time instant is unnecessary. ...

Mesh manipulation is central to computational fluid dynamics. However, creating appropriate computational meshes often involves substantial manual intervention that has to be repeated each time the target shape changes. To address this problem, we propose ...

Recent works have shown that 3D shape of non-rigid surfaces can be accurately retrieved from a single im- age given a set of 3D-to-2D correspondences between that image and another one for which the shape is known. However, existing approaches assume that ...

In this paper, we introduce a local image descriptor, DAISY, which is very efficient to compute densely. We also present an EM based algorithm to compute dense depth and occlusion maps from wide baseline image pairs using this descriptor. This yields much ...

This paper proposes a relational learning based approach for discovering strategies in volleyball matches based on optical tracking data. In contrast to most existing methods, our approach permits discovering patterns that account for both spatial (that is, partial configurations of the players on the court) and temporal , that is, the order of events and positions, aspects of the game. We analyze both the men’s and women’s final match from the 2014 FIVB Volleyball World Championships, and are able to ident

Unsigned Distance Fields (UDFs) can be used to represent non-watertight surfaces. However, current approaches to converting them into explicit meshes tend to either be expensive or to degrade the accuracy. Here, we extend the marching cube algorithm to han ...

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 ...

Probabilistic atlases (PAs) have long been used in standard segmentation approaches and, more recently, in conjunction with Convolutional Neural Networks (CNNs). However, their use has been restricted to relatively standardized structures such as the brain ...

Recovering multiple point light sources from a sparse set of photographs in which objects of unknown texture can move is challenging. This is because both diffuse and specular reflections appear to slide across surfaces, which is a well known physical fact ...

In this paper we want to start the discussion on whether image based 3-D modelling techniques can possibly be used to replace LIDAR systems for outdoor 3D data acquisition. Two main issues have to be addressed in this context: (i) camera calibration (inter ...

Pascal Fua

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Pose Priors for Simultaneously Solving Alignment and Correspondence

Large occlusion completion using normal maps

Image Summaries using Database Saliency

Gradient Response Maps for Real-Time Detection of Textureless Objects

3D pose refinement from reflections

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

Active Learning and Proofreading for Delineation of Curvilinear Structures

Capturing 3D Stretchable Surfaces from Single Images in Closed Form

Segmentation-driven 6D Object Pose Estimation

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

Long Term Motion Prediction Using Keyposes

Latent Representation of Computational Fluid Dynamics Meshes and Application to Airfoil Aerodynamics

Simultaneous Pose, Correspondence and Non-Rigid Shape

Daisy: An Efficient Dense Descriptor Applied to Wide Baseline Stereo

Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques

MeshUDF: Fast and Differentiable Meshing of Unsigned Distance Field Networks

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

Probabilistic Atlases to Enforce Topological Constraints

Retrieving multiple light sources in the presence of specular reflections and texture

On Benchmarking Camera Calibration and Multi-View Stereo for High Resolution Imagery