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Grigory Antipov
Grigory Antipov
Orange Labs
Verified email at orange.com
Title
Cited by
Cited by
Year
Face aging with conditional generative adversarial networks
G Antipov, M Baccouche, JL Dugelay
2017 IEEE international conference on image processing (ICIP), 2089-2093, 2017
4952017
Learned vs. hand-crafted features for pedestrian gender recognition
G Antipov, SA Berrani, N Ruchaud, JL Dugelay
Proceedings of the 23rd ACM international conference on Multimedia, 1263-1266, 2015
1292015
Minimalistic CNN-based ensemble model for gender prediction from face images
G Antipov, SA Berrani, JL Dugelay
Pattern recognition letters 70, 59-65, 2016
1252016
Effective training of convolutional neural networks for face-based gender and age prediction
G Antipov, M Baccouche, SA Berrani, JL Dugelay
Pattern Recognition 72, 15-26, 2017
1162017
Apparent Age Estimation from Face Images Combining General and Children-Specialized Deep Learning Models
G Antipov, M Baccouche, SA Berrani, JL Dugelay
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops …, 2016
942016
Roses are red, violets are blue... but should vqa expect them to?
C Kervadec, G Antipov, M Baccouche, C Wolf
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
272021
Boosting cross-age face verification via generative age normalization
G Antipov, M Baccouche, JL Dugelay
2017 IEEE International Joint Conference on Biometrics (IJCB), 191-199, 2017
202017
The impact of privacy protection filters on gender recognition
N Ruchaud, G Antipov, P Korshunov, JL Dugelay, T Ebrahimi, SA Berrani
Applications of digital image processing XXXVIII 9599, 959906, 2015
92015
How transferable are reasoning patterns in vqa?
C Kervadec, T Jaunet, G Antipov, M Baccouche, R Vuillemot, C Wolf
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
82021
Weak supervision helps emergence of word-object alignment and improves vision-language tasks
C Kervadec, G Antipov, M Baccouche, C Wolf
arXiv preprint arXiv:1912.03063, 2019
72019
Supervising the transfer of reasoning patterns in vqa
C Kervadec, C Wolf, G Antipov, M Baccouche, M Nadri
Advances in Neural Information Processing Systems 34, 2021
32021
Estimating semantic structure for the VQA answer space
C Kervadec, G Antipov, M Baccouche, C Wolf
arXiv preprint arXiv:2006.05726, 2020
32020
VisQA: X-raying Vision and Language Reasoning in Transformers
T Jaunet, C Kervadec, R Vuillemot, G Antipov, M Baccouche, C Wolf
IEEE Transactions on Visualization and Computer Graphics 28 (1), 976-986, 2021
22021
Mining Users Skills Development From Interaction Traces: an exploratory study
A Belin, G Antipov, J Blanchard, F Guillet, Y Prié
Data Mining and Knowledge Discovery 1 (3), 259-289, 1997
21997
Are E2E ASR models ready for an industrial usage?
V Vielzeuf, G Antipov
arXiv preprint arXiv:2112.12572, 2021
12021
Automatic quality assessment for audio-visual verification systems. The LOVe submission to NIST SRE challenge 2019
G Antipov, N Gengembre, OL Blouch, GL Lan
arXiv preprint arXiv:2008.05889, 2020
12020
Deep learning for semantic description of visual human traits
G Antipov
Télécom ParisTech, 2017
12017
An experimental study of the vision-bottleneck in VQA
P Marza, C Kervadec, G Antipov, M Baccouche, C Wolf
arXiv preprint arXiv:2202.06858, 2022
2022
Apprentissage profond pour la description sémantique des traits visuels humains
G Antipov
Paris, ENST, 2017
2017
Deep learning for semantic description of visual human traits.(Apprentissage profond pour la description sémantique des traits visuels humains)
G Antipov
2017
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