Matthieu Cord

I am Professor at UPMC-Sorbonne Universities, Researcher in the MLIA team of the LIP6 lab at UPMC, Scientific project manager at CNRS (INS2I), and IUF junior 2009.

My research interests include: Image Processing, Computer Vision, Deep Learning, Pattern Recognition, Machine Learning for Multimedia and Computational Cooking.


Crazy about cooking, ready to cook anywhere, anything, even my computer. Currently cooking on ANR VISIIR PROJECT for Web food recipe filtering, and searching.

Try the demo food reco engine!

Recent publications

WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation

T. Durand, T. Mordan, N. Thome, M. Cord

CVPR (2017)

Paper Project page Supplementary

author = {Durand, Thibaut and Mordan, Taylor and Thome, Nicolas and Cord, Matthieu},
title = {{WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation}},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2017}

Deformable Part-based Fully Convolutional Network for Object Detection

T. Mordan, N. Thome, M. Cord, G. Henaff

BMVC, (on ArXiv) (2017)


MUTAN: Multimodal Tucker Fusion for Visual Question Answering

H. Ben-younes, R. Cadene, M. Cord, N. Thome

ICCV, (on ArXiv) (2017)

Paper Project page

Learning a Distance Metric from Relative Comparisons between Quadruplets of Images

M.T. Law, N. Thome, M. Cord

IJCV International Journal of Computer Vision (2016)

WELDON: Weakly Supervised Learning of Deep Convolutional Neural Networks

T. Durand, N. Thome, M. Cord

CVPR (2016)


Closed-Form Training of Mahalanobis Distance for Supervised Clustering

M.T. Law, Y Yu, M. Cord, E.P Xing

CVPR (oral) (2016)


MANTRA: Minimum Maximum Latent Structural SVM for Image Classification and Ranking

T. Durand, N. Thome, M. Cord

ICCV (2015)


Recipe Recognition with Large Multimodal Food Dataset

X. Wang, D. Kumar, N. Thome, M. Cord, F. Precioso

Cooking and Eating Activities in IEEE ICME (2015)


Sequentially Generated Instance-Dependent Image Representations for Classification

G. Dulac-Arnold, L. Denoyer, N. Thome, M. Cord, P. Gallinari

ICLR (2014)

Paper Video

Perceptual principles for video classification with Slow Feature Analysis

C. Thériault, N. Thome, M. Cord, P. Perez

IEEE Journal of Selected Topics in Signal Processing (2014)

See all my publications

Recent news


  • July ICCV 2017 paper on Tensor decomposition for VQA task accepted
  • July BMVC 2017 paper deep architecture for detection accepted
  • July CVPR WILDCAT paper presentation, VQA workshop (Challenge VQA2)
  • June Invited speaker, deep learning session in Big data advanced school, San Carlos, Brazil
  • Feb, 06: PhD def. of M. Paulin with J. Sivic, V. Lepetit, C. Wolf, F. Perronnin, J. Mairal, C. Schmid, Z. Harchaoui, M Cord (Reviewer)
  • Jan, 23: PhD def. of P. Kulkarni with P. Perez, F. Jurie, S. Canu, J. Zepeda, J. Verbeek, M Cord (Reviewer)


  • Dec., 2016: Invited speaker in Panel session in Future of Emerging Technologies – Memristors and Machine Learning, in 23rd IEEE International Conference on Electronics Circuits and Systems (ICECS), Monte Carlo, Monaco
  • Dec., 2: PhD def. of M. Chevalier with S. Canu, F. Bremond, C. Achard, P. Perez, M. Cord, G. Henaff, N. Thome
  • Oct., 2016: Invited talk in Symposium on Deep Learning and Artificial Intelligence, Tokyo, Japan
  • Oct., 2016: Invited talk Deep learning and weak supervision for visual recognition in GdR ISIS workshop
  • July/August, 2016: Deep learning chair in Brazil, UNICAMP University
  • June, 2016: 2 papers accepted at CVPR 2016
  • June 8, 2016: Talk at INRIA Thoth symposium on Computer Vision and Deep Learning
  • June 7, 2016: HDR defense of Jakob Verbeek with M. Cord (reviewer), A. Zisserman, E. Gaussier, E. Learned-Miller, C. Schmid, T. Tuytelaars.
  • May 19, 2016: Talk at I3S lab. on deep and weak supervision
  • April 14, 2016: Half Day Deep learning Workshop (2nd edition) with GdR-ISIS at UPMC
    • Introduction by M. Cord
    • Plenary Talk of Yann LeCun (Facebook AI research, NYU, College de France) on predictive learning
    • Poster session

News history


(+33) 1 44 27 71 39
Fax: (+33) 1 44 27 70 00
4, place Jussieu
75005 Paris, France