Seguir
Nicolas Thome
Nicolas Thome
Professor of Computer Science, Sorbonne University, France
Dirección de correo verificada de sorbonne-universite.fr - Página principal
Título
Citado por
Citado por
Año
Mutan: Multimodal tucker fusion for visual question answering
H Ben-Younes, R Cadene, M Cord, N Thome
Proceedings of the IEEE international conference on computer vision, 2612-2620, 2017
7672017
Wildcat: Weakly supervised learning of deep convnets for image classification, pointwise localization and segmentation
T Durand, T Mordan, N Thome, M Cord
Proceedings of the IEEE conference on computer vision and pattern …, 2017
4132017
Murel: Multimodal relational reasoning for visual question answering
R Cadene, H Ben-Younes, M Cord, N Thome
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
3602019
Addressing failure prediction by learning model confidence
C Corbière, N Thome, A Bar-Hen, M Cord, P Pérez
Advances in Neural Information Processing Systems 32, 2019
3442019
Disentangling physical dynamics from unknown factors for unsupervised video prediction
VL Guen, N Thome
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
3402020
U-net transformer: Self and cross attention for medical image segmentation
O Petit, N Thome, C Rambour, L Themyr, T Collins, L Soler
Machine Learning in Medical Imaging: 12th International Workshop, MLMI 2021 …, 2021
2972021
Pooling in image representation: The visual codeword point of view
S Avila, N Thome, M Cord, E Valle, ADA AraúJo
Computer Vision and Image Understanding 117 (5), 453-465, 2013
2702013
Block: Bilinear superdiagonal fusion for visual question answering and visual relationship detection
H Ben-Younes, R Cadene, N Thome, M Cord
Proceedings of the AAAI conference on artificial intelligence 33 (01), 8102-8109, 2019
2622019
Recipe recognition with large multimodal food dataset
X Wang, D Kumar, N Thome, M Cord, F Precioso
2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 1-6, 2015
2592015
Cross-modal retrieval in the cooking context: Learning semantic text-image embeddings
M Carvalho, R Cadène, D Picard, L Soulier, N Thome, M Cord
The 41st International ACM SIGIR Conference on Research & Development in …, 2018
2422018
Weldon: Weakly supervised learning of deep convolutional neural networks
T Durand, N Thome, M Cord
Proceedings of the IEEE conference on computer vision and pattern …, 2016
2092016
Augmenting physical models with deep networks for complex dynamics forecasting
Y Yin, V Le Guen, J Dona, E de Bézenac, I Ayed, N Thome, P Gallinari
Journal of Statistical Mechanics: Theory and Experiment 2021 (12), 124012, 2021
1792021
A real-time, multiview fall detection system: A LHMM-based approach
N Thome, S Miguet, S Ambellouis
IEEE transactions on circuits and systems for video technology 18 (11), 1522 …, 2008
1752008
Shape and time distortion loss for training deep time series forecasting models
V Le Guen, N Thome
Advances in neural information processing systems 32, 2019
1712019
Gossip training for deep learning
M Blot, D Picard, M Cord, N Thome
arXiv preprint arXiv:1611.09726, 2016
1322016
Learning deep hierarchical visual feature coding
H Goh, N Thome, M Cord, JH Lim
IEEE transactions on neural networks and learning systems 25 (12), 2212-2225, 2014
1222014
T-HOG: An effective gradient-based descriptor for single line text regions
R Minetto, N Thome, M Cord, NJ Leite, J Stolfi
Pattern recognition 46 (3), 1078-1090, 2013
1182013
Quadruplet-wise image similarity learning
MT Law, N Thome, M Cord
Proceedings of the IEEE international conference on computer vision, 249-256, 2013
1112013
Bossa: Extended bow formalism for image classification
S Avila, N Thome, M Cord, E Valle, AA Araújo
2011 18th IEEE International Conference on Image Processing, 2909-2912, 2011
1012011
Dynamic scene classification: Learning motion descriptors with slow features analysis
C Thériault, N Thome, M Cord
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
972013
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20