Marco Pedersoli
Marco Pedersoli
Associate professor, École de technologie supérieure, Montréal, Québec, Canada
Verified email at - Homepage
Cited by
Cited by
Face detection without bells and whistles
M Mathias, R Benenson, M Pedersoli, L Van Gool
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
A coarse-to-fine approach for fast deformable object detection
M Pedersoli, A Vedaldi, J Gonzalez, X Roca
Pattern Recognition 48 (5), 1844-1853, 2015
Weakly supervised object detection with convex clustering
H Bilen, M Pedersoli, T Tuytelaars
Proceedings of the IEEE conference on computer vision and pattern …, 2015
Areas of Attention for Image Captioning
M Pedersoli, T Lucas, C Schmid, J Verbeek
Proceedings of the IEEE International Conference on Computer Vision, 2017
Deep co-training for semi-supervised image segmentation
J Peng, G Estrada, M Pedersoli, C Desrosiers
Pattern Recognition 107, 107269, 2020
DeepProposals: Hunting objects and actions by cascading deep convolutional layers
A Ghodrati, A Diba, M Pedersoli, T Tuytelaars, L Van Gool
International Journal of Computer Vision 124, 115-131, 2017
A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses
M Boudiaf, J Rony, IM Ziko, E Granger, M Pedersoli, P Piantanida, ...
European conference on computer vision, 548-564, 2020
Weakly supervised object detection with posterior regularization
H Bilen, M Pedersoli, T Tuytelaars
British Machine Vision Conference 3, 4, 2014
Deep clustering: On the link between discriminative models and k-means
M Jabi, M Pedersoli, A Mitiche, IB Ayed
IEEE transactions on pattern analysis and machine intelligence 43 (6), 1887-1896, 2019
On the texture bias for few-shot cnn segmentation
R Azad, AR Fayjie, C Kauffmann, I Ben Ayed, M Pedersoli, J Dolz
Proceedings of the IEEE/CVF winter conference on applications of computer …, 2021
Semi-supervised few-shot learning for medical image segmentation
AR Feyjie, R Azad, M Pedersoli, C Kauffman, IB Ayed, J Dolz
arXiv preprint arXiv:2003.08462, 2020
Toward Real-Time Pedestrian Detection Based on a Deformable Template Model
M Pedersoli, J Gonzàlez, X Hu, X Roca
IEEE Transactions on Intelligent Transportation Systems, 1-10, 2014
Multimodal fusion with deep neural networks for audio-video emotion recognition
JDS Ortega, M Senoussaoui, E Granger, M Pedersoli, P Cardinal, ...
arXiv preprint arXiv:1907.03196, 2019
A joint cross-attention model for audio-visual fusion in dimensional emotion recognition
RG Praveen, WC de Melo, N Ullah, H Aslam, O Zeeshan, T Denorme, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
Self-paced contrastive learning for semi-supervised medical image segmentation with meta-labels
J Peng, P Wang, C Desrosiers, M Pedersoli
Advances in Neural Information Processing Systems 34, 16686-16699, 2021
Is 2D Information Enough For Viewpoint Estimation?.
A Ghodrati, M Pedersoli, T Tuytelaars
BMVC 101, 102, 2014
Self-paced and self-consistent co-training for semi-supervised image segmentation
P Wang, J Peng, M Pedersoli, Y Zhou, C Zhang, C Desrosiers
Medical Image Analysis 73, 102146, 2021
Recursive coarse-to-fine localization for fast object detection
M Pedersoli, J Gonzàlez, AD Bagdanov, JJ Villanueva
Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010
An attention model for group-level emotion recognition
A Gupta, D Agrawal, H Chauhan, J Dolz, M Pedersoli
Proceedings of the 20th ACM International Conference on Multimodal …, 2018
Towards automatic image editing: Learning to see another you
A Ghodrati, X Jia, M Pedersoli, T Tuytelaars
arXiv preprint arXiv:1511.08446, 2015
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