| Face aging with conditional generative adversarial networks G Antipov, M Baccouche, JL Dugelay 2017 IEEE international conference on image processing (ICIP), 2089-2093, 2017 | 834 | 2017 |
| 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 | 159 | 2017 |
| 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 | 156 | 2015 |
| Minimalistic CNN-based ensemble model for gender prediction from face images G Antipov, SA Berrani, JL Dugelay Pattern recognition letters 70, 59-65, 2016 | 153 | 2016 |
| 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 | 120 | 2016 |
| 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 | 82 | 2021 |
| 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 | 30 | 2021 |
| 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 | 25 | 2017 |
| 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 | 24 | 2021 |
| 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 | 13 | 2019 |
| 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, 36-47, 2015 | 10 | 2015 |
| 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, 18256-18267, 2021 | 8 | 2021 |
| Estimating semantic structure for the VQA answer space C Kervadec, G Antipov, M Baccouche, C Wolf arXiv preprint arXiv:2006.05726, 2020 | 7 | 2020 |
| Are E2E ASR models ready for an industrial usage? V Vielzeuf, G Antipov arXiv preprint arXiv:2112.12572, 2021 | 6 | 2021 |
| 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 | 4 | 2020 |
| Deep learning for semantic description of visual human traits G Antipov Télécom ParisTech, 2017 | 2 | 2017 |
| 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 | 2 | 1997 |
| 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 Télécom ParisTech, France, 2017 | | 2017 |
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