| Training data-efficient image transformers & distillation through attention H Touvron, M Cord, M Douze, F Massa, A Sablayrolles, H Jégou Thirty-eighth International Conference on Machine Learning (ICML), 2021 | 1000 | 2021 |
| Advent: Adversarial entropy minimization for domain adaptation in semantic segmentation TH Vu, H Jain, M Bucher, M Cord, P Pérez CVPR Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 517 | 2019 |
| Mutan: Multimodal tucker fusion for visual question answering H Ben-Younes, R Cadene, M Cord, N Thome ICCV 2017 Proc. IEEE International Conference Computer Vision, 2017 | 475 | 2017 |
| Machine learning techniques for multimedia M Cord, P Cunningham Book Springer, 2008 | 330* | 2008 |
| Wildcat: Weakly supervised learning of deep convnets for image classification, pointwise localization and segmentation T Durand, T Mordan, N Thome, M Cord CVPR 2017 Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 306 | 2017 |
| Boosting Few-Shot Visual Learning with Self-Supervision S Gidaris, A Bursuc, N Komodakis, P Pérez, M Cord ICCV 2019 arXiv preprint arXiv:1906.05186, 2019 | 229 | 2019 |
| Pooling in image representation: The visual codeword point of view S Avila, N Thome, M Cord, E Valle, ADA AraúJo CVIU Computer Vision and Image Understanding 117 (5), 453-465, 2013 | 227 | 2013 |
| MUREL: Multimodal Relational Reasoning for Visual Question Answering R Cadene, H Ben-Younes, M Cord, N Thome CVPR arXiv preprint arXiv:1902.09487, 2019 | 195 | 2019 |
| Going deeper with image transformers H Touvron, M Cord, A Sablayrolles, G Synnaeve, H Jégou International Conference on Computer Vision (ICCV), 2021 | 169 | 2021 |
| Weldon: Weakly supervised learning of deep convolutional neural networks T Durand, N Thome, M Cord CVPR 2016 Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 165 | 2016 |
| Supervised learning P Cunningham, M Cord, SJ Delany Machine learning techniques for multimedia, 21-49, 2008 | 159 | 2008 |
| RUBi: Reducing Unimodal Biases in Visual Question Answering R Cadene, C Dancette, H Ben-younes, M Cord, D Parikh NeurIPS 2019 -- arXiv preprint arXiv:1906.10169, arXiv preprint arXiv:1906 …, 2019 | 151 | 2019 |
| 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 | 141 | 2015 |
| Cross-Modal Retrieval in the Cooking Context: Learning Semantic Text-Image Embeddings M Carvalho, R Cadène, D Picard, L Soulier, N Thome, M Cord ACM SIGIR arXiv preprint arXiv:1804.11146, 2018 | 139 | 2018 |
| Active learning methods for interactive image retrieval PH Gosselin, M Cord IEEE Transactions on Image Processing 17 (7), 1200-1211, 2008 | 137 | 2008 |
| BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection H Ben-Younes, R Cadene, N Thome, M Cord AAAI conference 2019, 2019 | 118 | 2019 |
| PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning A Douillard, M Cord, C Ollion, T Robert, E Valle ECCV 2020, 2020 | 113 | 2020 |
| Learning deep hierarchical visual feature coding H Goh, N Thome, M Cord, JH Lim TNNLS IEEE transactions on neural networks and learning systems journal 25 …, 2014 | 113 | 2014 |
| 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 | 107 | 2013 |
| Addressing Failure Prediction by Learning Model Confidence C Corbière, N Thome, A Bar-Hen, M Cord, P Pérez NeurIPS 2019 -- arXiv preprint arXiv:1910.04851, 2019 | 106 | 2019 |
Nicolas ThomeProfessor of Computer Science, Cnam Paris, FranceEmail verificata su cnam.fr
