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
1722017
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
1162016
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
372015
Learning a Deep ConvNet for Multi-label Classification with Partial Labels
T Durand, N Mehrasa, G Mori
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
282019
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
162019
Exploiting Negative Evidence for Deep Latent Structured Models
T Durand, N Thome, M Cord
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018
112018
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
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 Conference on Computer Vision and Pattern …, 2019
82019
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
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
62014
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
52018
Weakly supervised learning for visual recognition
T Durand
Université Pierre et Marie Curie, 2017
52017
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
22020
Point Process Flows
N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ...
arXiv preprint arXiv:1910.08281, 2019
12019
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
2020
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
2020
Learning User Representations for Open Vocabulary Image Hashtag Prediction
T Durand
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
2020
Arbitrarily-conditioned Data Imputation
M Carvalho, T Durand, J He, N Mehrasa, G Mori
2019
Learning from Partially-Observed Multimodal Data with Variational Autoencoders
Y Gong, H Hajimirsadeghi, J He, M Nawhal, T Durand, G Mori
2019
LayoutVAE: Stochastic Scene Layout Generation from a Label Set
A Abdu Jyothi, T Durand, J He, L Sigal, G Mori
arXiv preprint arXiv:1907.10719, 2019
2019
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