Thibaut Durand

According to our database, Thibaut Durand authored at least 18 papers between 2013 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Training a Vision Transformer from scratch in less than 24 hours with 1 GPU.

Saghar Irandoust, Thibaut Durand, Yunduz Rakhmangulova, Wenjie Zi, Hossein Hajimirsadeghi

CoRR, 2022

2021

Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data.

Yu Gong, Hossein Hajimirsadeghi, Jiawei He, Thibaut Durand, Greg Mori

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Learning User Representations for Open Vocabulary Image Hashtag Prediction.

Thibaut Durand

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Exploiting Negative Evidence for Deep Latent Structured Models.

Thibaut Durand, Nicolas Thome, Matthieu Cord

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Point Process Flows.

Nazanin Mehrasa, Ruizhi Deng, Mohamed Osama Ahmed, Bo Chang, Jiawei He, Thibaut Durand, Marcus A. Brubaker, Greg Mori

CoRR, 2019

LayoutVAE: Stochastic Scene Layout Generation From a Label Set.

Akash Abdu Jyothi, Thibaut Durand, Jiawei He, Leonid Sigal, Greg Mori

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

A Variational Auto-Encoder Model for Stochastic Point Processes.

Nazanin Mehrasa, Akash Abdu Jyothi, Thibaut Durand, Jiawei He, Leonid Sigal, Greg Mori

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Learning a Deep ConvNet for Multi-Label Classification With Partial Labels.

Thibaut Durand, Nazanin Mehrasa, Greg Mori

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Variational Selective Autoencoder.

Yu Gong, Hossein Hajimirsadeghi, Jiawei He, Megha Nawhal, Thibaut Durand, Greg Mori

Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019

2018

SyMIL: MinMax Latent SVM for Weakly Labeled Data.

Thibaut Durand, Nicolas Thome, Matthieu Cord

IEEE Trans. Neural Networks Learn. Syst., 2018

2017

Weakly supervised learning for visual recognition. (Apprentissage faiblement supervisé pour la reconnaissance visuelle).

Thibaut Durand

PhD thesis, 2017

WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation.

Thibaut Durand, Taylor Mordan, Nicolas Thome, Matthieu Cord

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Synthetic Sound Event Detection based on MFCC.

Juana M. Gutiérrez-Arriola, Rubén Fraile, Alexander Camacho, Thibaut Durand, Jaime L. Jarrín, Shirley R. Mendoza

Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events, 2016

WELDON: Weakly Supervised Learning of Deep Convolutional Neural Networks.

Thibaut Durand, Nicolas Thome, Matthieu Cord

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

MANTRA: Minimum Maximum Latent Structural SVM for Image Classification and Ranking.

Thibaut Durand, Nicolas Thome, Matthieu Cord

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

Incremental learning of latent structural SVM for weakly supervised image classification.

Thibaut Durand, Nicolas Thome, Matthieu Cord, David Picard

Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

Semantic pooling for image categorization using multiple kernel learning.

Thibaut Durand, David Picard, Nicolas Thome, Matthieu Cord

Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

2013

Image classification using object detectors.

Thibaut Durand, Nicolas Thome, Matthieu Cord, Sandra Eliza Fontes de Avila

Proceedings of the IEEE International Conference on Image Processing, 2013