Jakob Verbeek

发表

Image Classification with the Fisher Vector: Theory and Practice

Thomas Mensink, Florent Perronnin, Jorge Sánchez, 2013, International Journal of Computer Vision.

New Results - Semi-supervised learning and structuring of visual models

Cordelia Schmid, Hakan Cevikalp, Matthieu Guillaumin, 2008 .

Distilled Hierarchical Neural Ensembles with Adaptive Inference Cost pdf

Jakob Verbeek, Adria Ruiz, 2020, ArXiv.

Predicting Deeper into the Future of Semantic Segmentation

Yann LeCun, Camille Couprie, Pauline Luc, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

The AXES submissions at TRECVID 2013

Cordelia Schmid, Noel E. O'Connor, Danila Potapov, 2013, TRECVID.

New Results - Visual object recognition

Cordelia Schmid, Joost van de Weijer, Martial Hebert, 2007 .

New Results - Learning and structuring of visual models

Cordelia Schmid, Matthieu Guillaumin, Gabriela Csurka, 2010 .

Hierarchical Scene Coordinate Classification and Regression for Visual Localization

Juho Kannala, Yi Zhao, Jakob Verbeek, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Discrete Point Flow Networks for Efficient Point Cloud Generation

Edmond Boyer, Jakob Verbeek, Roman Klokov, 2020, ECCV.

Rodent behavior annotation from video

Jakob Verbeek, J. Verbeek, 2005 .

Improved Training Techniques for Online Neural Machine Translation

Jakob Verbeek, Laurent Besacier, Maha Elbayad, 2019 .

Software and Platforms - Video descriptors

Cordelia Schmid, Heng Wang, Dan Oneata, 2013 .

New Results - Visual recognition in images

Cordelia Schmid, Trevor Darrell, C. V. Jawahar, 2013 .

Procrustes Analysis to Coordinate Mixtures of Probabilistic Principal Component Analyzers

Jakob Verbeek, J. Verbeek, 2002 .

Software and Platforms - Object category localization

Cordelia Schmid, Matthijs Douze, Ramazan Gokberk Cinbis, 2013 .

Anytime Inference with Distilled Hierarchical Neural Ensembles

Jakob Verbeek, Adria Ruiz, J. Verbeek, 2020, AAAI.

Systems and extraction processes using probabilistic feedback information relevant transmedia

Gabriela Csurka, Thomas Mensink, Jakob Verbeek, 2011 .

Hierarchical Joint Scene Coordinate Classification and Regression for Visual Localization pdf

Juho Kannala, Jakob Verbeek, Xiaotian Li, 2019, ArXiv.

Semi-supervised learning with gaussian fields

Nikos A. Vlassis, Jakob Verbeek, N. Vlassis, 2005 .

Reference-based Variational Autoencoders

Xavier Binefa, Jakob Verbeek, Adria Ruiz, 2019 .

Efficient Wait-k Models for Simultaneous Machine Translation pdf

Jakob Verbeek, Laurent Besacier, Maha Elbayad, 2020, INTERSPEECH.

The generative self-organizing map: a probabilistic generalization of Kohonen's SOM

Ben Kröse, Jakob Verbeek, Nikos Vlassis, 2002 .

Action Localization with Approximately

Cordelia Schmid, Dan Oneata, Jakob Verbeek, 2014 .

Probabilistic Reconstruction Networks for 3D Shape Inference from a Single Image

Edmond Boyer, Jakob Verbeek, Roman Klokov, 2019, BMVC.

New Software and Platforms - CoNFab: COnvolutional Neural FABric

Jakob Verbeek, Shreyas Saxena, 2016 .

New Results - Supervised methods for visual object recognition and localization

Cordelia Schmid, Matthieu Guillaumin, Tingting Jiang, 2009 .

Adaptative Inference Cost With Convolutional Neural Mixture Models

Jakob Verbeek, Adria Ruiz, J. Verbeek, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Meta-Learning with Shared Amortized Variational Inference

Ekaterina Iakovleva, Karteek Alahari, Jakob Verbeek, 2020, ICML.

Understanding Priors in Bayesian Neural Networks at the Unit Level

Pablo Mesejo, Julyan Arbel, Jakob Verbeek, 2018, ICML.

DualConv: Dual Mesh Convolutional Networks for Shape Correspondence pdf

Edmond Boyer, Jakob Verbeek, Adnane Boukhayma, 2021, ArXiv.

Learning to Rank and Quadratic Assignment

Thomas Mensink, Tibério S. Caetano, Jakob Verbeek, 2011, NIPS 2011.

Using a sample-dependent coding scheme for two-part MDL

Jakob Verbeek, J. Verbeek, 1999 .

Locally Linear Generative Topographic Mapping

Ben Kröse, Jakob Verbeek, Nikos Vlassis, 2002 .

Non-linear feature extaction by the coordination of mixture models

Jakob Verbeek, Nikos Vlassis, Ben J. A. Krse, 2003 .

Efficient greedy learning of Gaussian mixtures

Ben Kröse, Jakob Verbeek, Nikos Vlassis, 2001 .

Greedy Gaussian mixture learning for texture segmentation

Ben Kröse, Jakob Verbeek, Nikos Vlassis, 2001 .

Compressed Fisher Vectors for Large-Scale Image Classification

Thomas Mensink, Florent Perronnin, Jorge Sánchez, 2013 .

A variational (E)(M) algorithm for large-scale mixture modeling

Nikos A. Vlassis, Jakob Verbeek, Jan R. J. Nunnink, 2003 .