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Vincent Lepetit

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Related publications (76)

Page 3 of 4

Fast Non-Rigid Surface Detection, Registration and Realistic Augmentation

Pascal Fua, Vincent Lepetit, Julien Pilet

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 d ...

2008

BRIEF: Binary Robust Independent Elementary Features

Pascal Fua, Vincent Lepetit, Christoph Strecha, Michael Calonder

We propose to use binary strings as an efficient feature point descriptor, which we call BRIEF. We show that it is highly discriminative even when using relatively few bits and can be computed using simple intensity difference tests. Furthermore, the descr ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2010

Learning Latent Representations of 3D Human Pose with Deep Neural Networks

Pascal Fua, Mathieu Salzmann, Vincent Lepetit, Bugra Tekin

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

2018

Flying Objects Detection from a Single Moving Camera

Pascal Fua, Vincent Lepetit, Artem Rozantsev

We propose an approach to detect flying objects such as UAVs and aircrafts when they occupy a small portion of the field of view, possibly moving against complex backgrounds, and are filmed by a camera that itself moves. Solving such a difficult problem re ...

2015

Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to Occlusions

Mathieu Salzmann, Vincent Lepetit, Yinlin Hu

We present a method that can recognize new objects and estimate their 3D pose in RGB images even under partial occlusions. Our method requires neither a training phase on these objects nor real images depicting them, only their CAD models. It relies on a s ...

IEEE COMPUTER SOC2022

On the Relevance of Sparsity for Image Classification

Pascal Fua, Vincent Lepetit, Engin Türetken, Germán González Serrano, Roberto Rigamonti, Matthew Brown, Fethallah Benmansour

In this paper we empirically analyze the importance of sparsifying representations for classification purposes. We focus on those obtained by convolving images with linear filters, which can be either hand designed or learned, and perform extensive experim ...

Elsevier2014

Learning Image Descriptors with the Boosting-Trick

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

In this paper we apply boosting to learn complex non-linear local visual feature representations, drawing inspiration from its successful application to visual object detection. The main goal of local feature descriptors is to distinctively repre- sent a s ...

2012

Supervised Feature Learning for Curvilinear Structure Segmentation

Pascal Fua, Vincent Lepetit, Roberto Rigamonti, Carlos Joaquin Becker

Springer2013

Fast Keypoint Recognition in Ten Lines of Code

Pascal Fua, Vincent Lepetit, Mustafa Özuysal

While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. In this paper, we show that formulating the problem in ...

IEEE2007

From Canonical Poses to 3D Motion Capture Using a Single Camera

Pascal Fua, Vincent Lepetit

We combine detection and tracking techniques to achieve robust 3D motion recovery of people seen from arbitrary viewpoints by a single and potentially moving camera. We rely on detecting key postures, which can be done reliably, using a motion model to inf ...

Institute of Electrical and Electronics Engineers2010

Combining Geometric and Appearance Priors for Robust Homography Estimation

Pascal Fua, Vincent Lepetit, Mustafa Özuysal

The homography between pairs of images are typically computed from the correspondence of keypoints, which are established by using image descriptors. When these descriptors are not reliable, either because of repetitive patterns or large amounts of clutter ...

2010

Fast Keypoint Recognition using Random Ferns

Pascal Fua, Vincent Lepetit, Michael Calonder, Mustafa Özuysal

2010

Closed-Form Solution to Non-rigid 3D Surface Registration

Pascal Fua, Mathieu Salzmann, Vincent Lepetit

We present a closed-form solution to the problem of recovering the 3D shape of a non-rigid inelastic surface from 3D-to-2D correspondences. This lets us detect and reconstruct such a, surface by matching individual images against a reference configuration, ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2008

Fast Ray Features for Learning Irregular Shapes

Vincent Lepetit, Kevin Smith

We introduce a new class of image features, the Ray feature set, that consider image characteristics at distant contour points, capturing information which is difficult to represent with standard feature sets. This property allows Ray features to efficient ...

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

Direct Prediction of 3D Body Poses from Motion Compensated Sequences

Pascal Fua, Vincent Lepetit, Artem Rozantsev, Bugra Tekin

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

Real-Time Non-Rigid Surface Detection

Pascal Fua, Vincent Lepetit, Julien Pilet

2005

Pose Priors for Simultaneously Solving Alignment and Correspondence

Pascal Fua, Vincent Lepetit

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 ...

Springer2008

Gradient Response Maps for Real-Time Detection of Textureless Objects

Pascal Fua, Vincent Lepetit, Slobodan Ilic

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 ...

Institute of Electrical and Electronics Engineers2012

3D pose refinement from reflections

Pascal Fua, Mathieu Salzmann, Vincent Lepetit

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 ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008

Capturing 3D Stretchable Surfaces from Single Images in Closed Form

Pascal Fua, Mathieu Salzmann, Vincent Lepetit

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 ...

2009