489 citations · 1.9k across the 46 of their papers we have counts for
10 papers · 1 filter
Principled Parallel Mean-Field Inference for Discrete Random Fields
Pierre Baqué, Timur Bagautdinov, François Fleuret +1
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 i…
What Players do with the Ball: A Physically Constrained Interaction Modeling
Andrii Maksai, Xinchao Wang, Pascal Fua
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 t…
Direct Prediction of 3D Body Poses from Motion Compensated Sequences
Bugra Tekin, Artem Rozantsev, Vincent Lepetit +1
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 comput…
Learning to Assign Orientations to Feature Points
Kwang Moo Yi, Yannick Verdie, Pascal Fua +1
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 feat…
Introducing Geometry in Active Learning for Image Segmentation
Ksenia Konyushkova, Raphael Sznitman, Pascal Fua
We propose an Active Learning approach to training a segmentation classifier that exploits geometric priors to streamline the annotation process in 3D image volumes. To this end, w…
Predicting People's 3D Poses from Short Sequences
Bugra Tekin, Xiaolu Sun, Xinchao Wang +2
We propose an efficient approach to exploiting motion information from consecutive frames of a video sequence to recover the 3D pose of people. Instead of computing candidate poses…
Dense image registration and deformable surface reconstruction in presence of occlusions and minimal texture
Dat Tien Ngo, Sanghuyk Park, Anne Jorstad +3
Deformable surface tracking from monocular images is well-known to be under-constrained. Occlusions often make the task even more challenging, and can result in failure if the surf…
A provably convergent alternating minimization method for mean field inference
Pierre Baqué, Jean-Hubert Hours, François Fleuret +1
Mean-Field is an efficient way to approximate a posterior distribution in complex graphical models and constitutes the most popular class of Bayesian variational approximation meth…
Modeling Brain Circuitry over a Wide Range of Scales
Pascal Fua, Graham Knott
If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. El…
Globally Optimal Cell Tracking using Integer Programming
Engin Türetken, Xinchao Wang, Carlos Becker +2
We propose a novel approach to automatically tracking cell populations in time-lapse images. To account for cell occlusions and overlaps, we introduce a robust method that generate…