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Grigory Antipov
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2020 – today
- 2022
- [j3]Theo Jaunet, Corentin Kervadec, Romain Vuillemot, Grigory Antipov, Moez Baccouche, Christian Wolf:
VisQA: X-raying Vision and Language Reasoning in Transformers. IEEE Trans. Vis. Comput. Graph. 28(1): 976-986 (2022) - [i10]Pierre Marza, Corentin Kervadec, Grigory Antipov, Moez Baccouche, Christian Wolf:
An experimental study of the vision-bottleneck in VQA. CoRR abs/2202.06858 (2022) - 2021
- [c9]Corentin Kervadec, Grigory Antipov, Moez Baccouche, Christian Wolf:
Roses Are Red, Violets Are Blue... but Should VQA Expect Them To? CVPR 2021: 2776-2785 - [c8]Corentin Kervadec, Theo Jaunet, Grigory Antipov, Moez Baccouche, Romain Vuillemot, Christian Wolf:
How Transferable Are Reasoning Patterns in VQA? CVPR 2021: 4207-4216 - [c7]Corentin Kervadec, Christian Wolf, Grigory Antipov, Moez Baccouche, Madiha Nadri:
Supervising the Transfer of Reasoning Patterns in VQA. NeurIPS 2021: 18256-18267 - [i9]Theo Jaunet, Corentin Kervadec, Romain Vuillemot, Grigory Antipov, Moez Baccouche, Christian Wolf:
VisQA: X-raying Vision and Language Reasoning in Transformers. CoRR abs/2104.00926 (2021) - [i8]Corentin Kervadec, Theo Jaunet, Grigory Antipov, Moez Baccouche, Romain Vuillemot, Christian Wolf:
How Transferable are Reasoning Patterns in VQA? CoRR abs/2104.03656 (2021) - [i7]Corentin Kervadec, Christian Wolf, Grigory Antipov, Moez Baccouche, Madiha Nadri:
Supervising the Transfer of Reasoning Patterns in VQA. CoRR abs/2106.05597 (2021) - [i6]Valentin Vielzeuf, Grigory Antipov:
Are E2E ASR models ready for an industrial usage? CoRR abs/2112.12572 (2021) - 2020
- [c6]Corentin Kervadec, Grigory Antipov, Moez Baccouche, Christian Wolf:
Weak Supervision Helps Emergence of Word-Object Alignment and Improves Vision-Language Tasks. ECAI 2020: 2728-2735 - [c5]Grigory Antipov, Nicolas Gengembre, Olivier Le Blouch, Gaël Le Lan:
Automatic Quality Assessment for Audio-Visual Verification Systems. The LOVe Submission to NIST SRE Challenge 2019. INTERSPEECH 2020: 2237-2241 - [i5]Corentin Kervadec, Grigory Antipov, Moez Baccouche, Christian Wolf:
Roses Are Red, Violets Are Blue... but Should Vqa Expect Them To? CoRR abs/2006.05121 (2020) - [i4]Corentin Kervadec, Grigory Antipov, Moez Baccouche, Christian Wolf:
Estimating semantic structure for the VQA answer space. CoRR abs/2006.05726 (2020) - [i3]Grigory Antipov, Nicolas Gengembre, Olivier Le Blouch, Gaël Le Lan:
Automatic Quality Assessment for Audio-Visual Verification Systems. The LOVe submission to NIST SRE Challenge 2019. CoRR abs/2008.05889 (2020)
2010 – 2019
- 2019
- [i2]Corentin Kervadec, Grigory Antipov, Moez Baccouche, Christian Wolf:
Weak Supervision helps Emergence of Word-Object Alignment and improves Vision-Language Tasks. CoRR abs/1912.03063 (2019) - 2017
- [b1]Grigory Antipov:
Deep learning for semantic description of visual human traits. (Apprentissage profond pour la description sémantique des traits visuels humains). Télécom ParisTech, France, 2017 - [j2]Grigory Antipov, Moez Baccouche, Sid-Ahmed Berrani, Jean-Luc Dugelay:
Effective training of convolutional neural networks for face-based gender and age prediction. Pattern Recognit. 72: 15-26 (2017) - [c4]Grigory Antipov, Moez Baccouche, Jean-Luc Dugelay:
Boosting cross-age face verification via generative age normalization. IJCB 2017: 191-199 - [c3]Grigory Antipov, Moez Baccouche, Jean-Luc Dugelay:
Face aging with conditional generative adversarial networks. ICIP 2017: 2089-2093 - [i1]Grigory Antipov, Moez Baccouche, Jean-Luc Dugelay:
Face Aging With Conditional Generative Adversarial Networks. CoRR abs/1702.01983 (2017) - 2016
- [j1]Grigory Antipov, Sid-Ahmed Berrani, Jean-Luc Dugelay:
Minimalistic CNN-based ensemble model for gender prediction from face images. Pattern Recognit. Lett. 70: 59-65 (2016) - [c2]Grigory Antipov, Moez Baccouche, Sid-Ahmed Berrani, Jean-Luc Dugelay:
Apparent Age Estimation from Face Images Combining General and Children-Specialized Deep Learning Models. CVPR Workshops 2016: 801-809 - 2015
- [c1]Grigory Antipov, Sid-Ahmed Berrani, Natacha Ruchaud, Jean-Luc Dugelay:
Learned vs. Hand-Crafted Features for Pedestrian Gender Recognition. ACM Multimedia 2015: 1263-1266
Coauthor Index
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