Publications by Pascal Fua | EPFL Graph Search

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In this paper, we show that tracking multiple people whose paths may intersect can be formulated as a convex global optimization problem. Our proposed framework is designed to exploit image appearance cues to prevent identity switches. Our method is effect ...

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 ...

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 ...

Delineation of curvilinear structures is an important problem in Computer Vision with multiple practical applications. With the advent of Deep Learning, many current approaches on automatic delineation have focused on finding more powerful deep architectur ...

We present an active surface-based method for refining the boundary surfaces of mitochondria segmentation data. We exploit the fact that mitochondria have thick dark membranes, so referencing the image data at the inner membrane can help drive a more accur ...

With widening interests in using model organisms for reverse genetic approaches and biomimmetic micro-robotics, motility phenotyping of the nematode Caenorhabditis elegans is expanding across a growing array of locomotive environments. One ongoing bottlene ...

We present a fully automated approach to camera registration for augmented reality systems. It relies on purely passive vision techniques to solve the initialization and real-time tracking problems, given a rough CAD model of parts of the real scene. It does not require a controlled environment, for example placing markers. It handles arbitrarily complex models, occlusions, large camera displacements and drastic aspect changes. This is made possible by two major contributions: the first one is a fast recogn

For biologists studying the morphology of cells, Electron Microscopy (EM) is the method of choice with its {\it nm} resolution, across increasingly larger volumes. However, the time necessary to acquire such image series is long and often limits the amount ...

Computer vision applications have come to rely increasingly on superpixels in recent years, but it is not always clear what constitutes a good superpixel algorithm. In an effort to understand the benefits and drawbacks of existing methods, we empirically c ...

This paper advocates an implicit-surface representation of generic 3--D surfaces to take advantage of occluding edges in a very robust way. This lets us exploit silhouette constraints in uncontrolled environments that may involve occlusions and changing or cluttered backgrounds, which limit the applicability of most silhouette based methods. This desirable behavior is completely independent from the way the surface deformations are parametrized. To show this, we demonstrate our technique in three very diffe

We address the problem of determining where a photo was taken by estimating a full 6-DOF-plus-intrincs camera pose with respect to a large geo-registered 3D point cloud, bringing together research on image localization, landmark recognition, and 3D pose es ...

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 ...

We propose a novel approach to automatically track- ing cell populations in time-lapse images. To account for cell occlusions and overlaps, we introduce a robust method that generates an over-complete set of competing detection hypotheses. We then perform detection and tracking simultaneously on these hypotheses by solving to optimal- ity an integer program with only one type of flow variables. This eliminates the need for heuristics to handle missed detections due to occlusions and complex morphology. We d

Detecting car taillights at night is a task which can nowadays be accomplished very fast on cheap hardware. We rely on such detections to build a vision-based system that, coupling them in a rule-based fashion, is able to detect and track vehicles. This al ...

Estimating the metric height of a person from monocular imagery without additional assumptions is ill-posed. Existing solutions either require manual calibration of ground plane and camera geometry, special cameras, or reference objects of known size. We f ...

Eigendecomposition (ED) is widely used in deep networks. However, the backpropagation of its results tends to be numerically unstable, whether using ED directly or approximating it with the Power Iteration method, particularly when dealing with large matri ...

Existing connectivity-oriented performance measures rank road delineation algorithms inconsistently, which makes it difficult to decide which one is best for a given application. We show that these inconsistencies stem from design flaws that make the metri ...

We present a real-time method for detecting deformable surfaces, with no need whatsoever for a priori pose knowledge. Our method starts from a set of wide baseline point matches between an undeformed image of the object and the image in which it is to be detected. The matches are used not only to detect but also to compute a precise mapping from one to the other. The algorithm is robust to large deformations, lighting changes, motion blur, and occlusions. It runs at 10 frames per second on a 2.8 GHz PC and

A method for training a feature detector of an image processing device, including the steps of detecting features in the image to generate a score map, computing a center of mass on the score map to generate a location, extracting a patch from the image at ...

We introduce a learning-based approach to detect repeatable keypoints under drastic imaging changes of weather and lighting conditions to which state-of-the-art keypoint detectors are surprisingly sensitive. We first identify good keypoint candidates in mu ...

Pascal Fua

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Tracking Multiple People under Global Appearance Constraints

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

Learning to Assign Orientations to Feature Points

Beyond the Pixel-Wise Loss for Topology-Aware Delineation

Refining Mitochondria Segmentation in Electron Microscopy Imagery with Active Surfaces

Caenorhabditis elegant segmentation using texture-based models for motility phenotyping

Fully Automated and Stable Registration for Augmented Reality Applications

Efficient Scanning for EM Based Target Localization

SLIC Superpixels Compared to State-of-the-art Superpixel Methods

Implicit Meshes Make for Better Silhouettes

Worldwide Pose Estimation Using 3D Point Clouds

Principled Parallel Mean-Field Inference for Discrete Random Fields

Globally Optimal Cell Tracking using Integer Programming

Real-time vehicle tracking for driving assistance

Gravity as a Reference for Estimating a Person's Height from Video

Backpropagation-Friendly Eigendecomposition

Towards Reliable Evaluation of Algorithms for Road Network Reconstruction from Aerial Images

Real-time non-rigid surface detection

Method, system, and device for learned invariant feature transform for computer images

TILDE: A Temporally Invariant Learned DEtector