Grigory Antipov

According to our database1, Grigory Antipov authored at least 16 papers between 2015 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.



In proceedings 
PhD thesis 




VisQA: X-raying Vision and Language Reasoning in Transformers.
IEEE Trans. Vis. Comput. Graph., 2022

An experimental study of the vision-bottleneck in VQA.
CoRR, 2022

Are E2E ASR models ready for an industrial usage?
CoRR, 2021

Supervising the Transfer of Reasoning Patterns in VQA.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How Transferable Are Reasoning Patterns in VQA?
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Roses Are Red, Violets Are Blue... but Should VQA Expect Them To?
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Estimating semantic structure for the VQA answer space.
CoRR, 2020

Automatic Quality Assessment for Audio-Visual Verification Systems. The LOVe Submission to NIST SRE Challenge 2019.
Proceedings of the Interspeech 2020, 2020

Weak Supervision Helps Emergence of Word-Object Alignment and Improves Vision-Language Tasks.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Deep learning for semantic description of visual human traits. (Apprentissage profond pour la description sémantique des traits visuels humains).
PhD thesis, 2017

Effective training of convolutional neural networks for face-based gender and age prediction.
Pattern Recognit., 2017

Face aging with conditional generative adversarial networks.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

Boosting cross-age face verification via generative age normalization.
Proceedings of the 2017 IEEE International Joint Conference on Biometrics, 2017

Minimalistic CNN-based ensemble model for gender prediction from face images.
Pattern Recognit. Lett., 2016

Apparent Age Estimation from Face Images Combining General and Children-Specialized Deep Learning Models.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016

Learned vs. Hand-Crafted Features for Pedestrian Gender Recognition.
Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, MM '15, Brisbane, Australia, October 26, 2015