| 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 | 375 | 2017 |
| Learning a deep convnet for multi-label classification with partial labels T Durand, N Mehrasa, G Mori Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 198 | 2019 |
| 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 | 197 | 2016 |
| LayoutVAE: Stochastic scene layout generation from a label set AA Jyothi, T Durand, J He, L Sigal, G Mori Proceedings of the IEEE International Conference on Computer Vision, 9895-9904, 2019 | 95 | 2019 |
| A variational auto-encoder model for stochastic point processes N Mehrasa, AA Jyothi, T Durand, J He, L Sigal, G Mori Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 55 | 2019 |
| MANTRA: Minimum Maximum Latent Structural SVM for Image Classification and Ranking T Durand, N Thome, M Cord Proceedings of the IEEE International Conference on Computer Vision, 2713-2721, 2015 | 42 | 2015 |
| Exploiting Negative Evidence for Deep Latent Structured Models T Durand, N Thome, M Cord IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018 | 26 | 2018 |
| Higher runoff and soil detachment in rubber tree plantations compared to annual cultivation is mitigated by ground cover in steep mountainous Thailand M Neyret, H Robain, A De Rouw, JL Janeau, T Durand, J Kaewthip, ... Catena 189, 104472, 2020 | 16 | 2020 |
| Point Process Flows N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ... arXiv preprint arXiv:1910.08281, 2019 | 12 | 2019 |
| Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data Y Gong, H Hajimirsadeghi, J He, T Durand, G Mori International Conference on Artificial Intelligence and Statistics, 2377-2385, 2021 | 10 | 2021 |
| System and method for generative model for stochastic point processes N Mehrasa, AA Jyothi, T Durand, J He, M Gregory, M Ahmed, M Brubaker US Patent App. 16/685,327, 2020 | 10 | 2020 |
| Image classification using object detectors T Durand, N Thome, M Cord, S Avila ICIP 2013: IEEE International Conference on Image Processing, 4340-4344, 2013 | 10 | 2013 |
| Incremental Learning of Latent Structural SVM for Weakly Supervised Image Classification T Durand, N Thome, M Cord, D Picard IEEE International Conference on Image Processing 2014, 2014 | 9 | 2014 |
| Variational Selective Autoencoder Y Gong, H Hajimirsadeghi, J He, M Nawhal, T Durand, G Mori Symposium on Advances in Approximate Bayesian Inference, 1-17, 2020 | 8 | 2020 |
| SyMIL: MinMax Latent SVM for Weakly Labeled Data T Durand, N Thome, M Cord IEEE transactions on neural networks and learning systems 29 (12), 6099-6112, 2018 | 8 | 2018 |
| Weakly supervised learning for visual recognition T Durand Université Pierre et Marie Curie, 2017 | 8 | 2017 |
| SYSTEMS AND METHODS FOR LEARNING USER REPRESENTATIONS FOR OPEN VOCABULARY DATA SETS T Durand, G Mori US Patent App. 16/826,215, 2020 | 7 | 2020 |
| Semantic Pooling for Image Categorization using Multiple Kernel Learning T Durand, D Picard, N Thome, M Cord IEEE International Conference on Image Processing 2014, 2014 | 6 | 2014 |
| System and method for a convolutional neural network for multi-label classification with partial annotations T Durand, N Mehrasa, M Gregory US Patent App. 16/685,478, 2020 | 5 | 2020 |
| Learning User Representations for Open Vocabulary Image Hashtag Prediction T Durand Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 5 | 2020 |
Matthieu CordProfessor of Computer Science, Sorbonne UniversityVerified email at sorbonne-universite.fr
