Multi-Modal Contextual Analysis of Affective Dynamics in Collaborative Groups
D. Dresvyanskiy, M. Markitantov, J. Yu, H. Kaya and A. Karpov
Multi-modal Arousal and Valence Estimation under Noisy Conditions
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024, 2024
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D. Dresvyanskiy, M. Markitantov, J. Yu, P. Li, H. Kaya and A. Karpov
SUN Team's Contribution to ABAW 2024 Competition: Audio-visual Valence-Arousal Estimation and Expression Recognition
arXiv:2403.12609, 2024
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D. Dresvyanskiy, A. Karpov and W. Minker
The Importance of Data Diversity for Engagement Recognition Systems: a Cross-cultural Study
THe Proceedings of the 13th International Workshop on Spoken Dialogue Systems Technology (IWSDS 2023), 2023
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D. Dresvyanskiy, Y. Sinha, M. Busch, I. Siegert, A. Karpov and W. Minker
DyCoDa: A Multi-modal Data Collection of Multi-user Remote Survival Game Recordings
Speech and Computer, Springer International Publishing, pp. 163--177, 2022
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D. Dresvyanskiy, E. Ryumina, H. Kaya, M. Markitantov, A. Karpov and W. Minker
End-to-End Modeling and Transfer Learning for Audiovisual Emotion Recognition in-the-Wild
Multimodal Technologies and Interaction, Vol. 6, Num. 2, pp. 11, 2022
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E. Ryumina, D. Dresvyanskiy and A. Karpov
In search of a robust facial expressions recognition model: A large-scale visual cross-corpus study
Neurocomputing, Vol. 514, pp. 435-450, 2022
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D. Dresvyanskiy, W. Minker and A. Karpov
Deep Learning Based Engagement Recognition in Highly Imbalanced Data
Springer, International Conference on Speech and Computer, pp. 166-178, 2021
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D. Dresvyanskiy, I. Siegert, A. Karpov and W. Minker
Engagement Recognition Using Audio Channel Only
1st AI-Debate Workshop, 2021
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O. Verkholyak, D. Dresvyanskiy, A. Dvoynikova, D. Kotov, E. Ryumina, A. Velichko, D. Mamontov, W. Minker and A. Karpov
Ensemble-within-ensemble classification for escalation prediction from speech
INTERSPEECH, pp. 481-485, 2021
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D. Dresvyanskiy, T. Karaseva, V. Makogin, S. Mitrofanov, C. Redenbach and E. Spodarev
Statistics and Computing, Vol. 30, Num. 4, pp. 817-837, 2020
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D. Dresvyanskiy, E. Ryumina, H. Kaya, M. Markitantov, A. Karpov and W. Minker
An audio-video deep and transfer learning framework for multimodal emotion recognition in the wild
arXiv preprint arXiv:2010.03692, 2020
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D. Dresvyanskiy, O. Semenkina and P. Evgeny
Cooperative ant colony optimization for a hierarchical scheduling problem
IOP Conference Series: Materials Science and Engineering, Vol. 734, Num. 1, 2020
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M. Markitantov, D. Dresvyanskiy, D. Mamontov, H. Kaya, W. Minker and A. Karpov
Ensembling end-to-end deep models for computational paralinguistics tasks: ComParE 2020 Mask and Breathing Sub-challenges
pp. 2072-2076, 2020
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D. Dresvyanskiy, T. Karaseva, S. Mitrofanov, C. Redenbach, S. Schwaar, V. Makogin and E. Spodarev
Аpplication of clustering methods to anomaly detection in fibrous media
IOP Conference Series: Materials Science and Engineering, Vol. 537, pp. 7, June 2019
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H. Kaya, D. Fedotov, D. Dresvyanskiy, M. Doyran, D. Mamontov, M. Markitantov, A. Salah, E. Kavcar, A. Karpov and A. Ali Salah
Predicting depression and emotions in the cross-roads of cultures, para-linguistics, and non-linguistics
2019
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