Thibaut Durand
Thibaut Durand
Machine Learning Researcher, Borealis AI
Verified email at sfu.ca - Homepage
Title
Cited by
Cited by
Year
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
2342017
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
1412016
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
542019
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
412015
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
312019
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
162019
Exploiting Negative Evidence for Deep Latent Structured Models
T Durand, N Thome, M Cord
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018
152018
Image classification using object detectors
T Durand, N Thome, M Cord, S Avila
ICIP 2013: IEEE International Conference on Image Processing, 4340-4344, 2013
102013
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
72018
Weakly supervised learning for visual recognition
T Durand
Université Pierre et Marie Curie, 2017
72017
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
72014
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
62014
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
42020
Point Process Flows
N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ...
arXiv preprint arXiv:1910.08281, 2019
42019
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
12020
Learning User Representations for Open Vocabulary Image Hashtag Prediction
T Durand
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
12020
Using a Deep Convolutional Neural Network for Extracting Morphological Traits from Herbarium Images
Y Zhu, T Durand, E Chenin, M Pignal, P Gallinari, R Vignes-Lebbe
Biodiversity Information Science and Standards 1, e20400, 2017
12017
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
2021
SYSTEM AND METHOD FOR MACHINE LEARNING ARCHITECTURE FOR PARTIALLY-OBSERVED MULTIMODAL DATA
Y Gong, J HE, T Durand, M Nawhal, Y Cao, G Mori, SH Hajimirsadeghi
US Patent App. 16/882,074, 2020
2020
SYSTEMS AND METHODS FOR LEARNING USER REPRESENTATIONS FOR OPEN VOCABULARY DATA SETS
T Durand, G Mori
US Patent App. 16/826,215, 2020
2020
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