I am working at the Pierre and Marie Curie University in Paris, at the LIP6 lab, in the MLIA team managed by Patrick Gallinari. Our team, supervised by Matthieu Cord, is focusing on Computer Vision research and is of course taking the deep learning turn. Here are some example of publications by our team:
- WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation. T Durand, T Mordan, N Thome, M Cord. CVPR 2017.
- LR-CNN for Fine-grained Classification with Varying Resolution., M Chevalier, N Thome, M Cord, J Fournier, G Henaff, E Dusch. ICIP 2015.
- Recipe Recognition with Large Multimodal Food Dataset. X Wang, D Kumar, N Thome, M Cord, F Precioso ICMEW 2015.
- MANTRA: Minimum Maximum Latent Structural SVM for Image Classification and Ranking. T Durand, N Thome, M Cord. ICCV 2015.
- Sequentially Generated Instance-Dependent Image Representations for Classification. G Dulac-Arnold, L Denoyer, N Thome, M Cord, P Gallinari. ICLR 2014.
- Fantope Regularization in Metric Learning. MT Law, N Thome, M Cord. CVPR 2014.
- Learning deep hierarchical visual feature coding. H Goh, N Thome, M Cord, JH Lim. TNNLS 2014.
- Top-Down Regularization of Deep Belief Networks. H Goh, N Thome, M Cord, JH Lim. NIPS 2013.
- Pooling in image representation: The visual codeword point of view. S Avila, N Thome, M Cord, E Valle, ADA Araújo. CVIU 2013.
- Quadruplet-wise Image Similarity Learning. M Law, N Thome, M Cord. ICCV 2013.
- Unsupervised and Supervised Visual Codes with Restricted Boltzmann Machines. H Goh, N Thome, M Cord, JH Lim. ECCV 2012.
My research interests are broad and goes from supervised deep learning for image classification to semantic representation learning for text and images and deep recurrent neural networks.
Currently, I am working on developing new architecture of convolutional neural networks for image classification using semi-supervised learning, and for this matter I have a particular interest on generative models of images (VAEs, GANs, etc.).