4 citations · 8 across the 4 of their papers we have counts for
5 papers
Team RAS in 10th ABAW Competition: Multimodal Valence and Arousal Estimation Approach
Elena Ryumina, Maxim Markitantov, Alexandr Axyonov +4
Continuous emotion recognition in terms of valence and arousal under in-the-wild (ITW) conditions remains a challenging problem due to large variations in appearance, head pose, il…
SUN Team's Contribution to ABAW 2024 Competition: Audio-visual Valence-Arousal Estimation and Expression Recognition
Denis Dresvyanskiy, Maxim Markitantov, Jiawei Yu +3
As emotions play a central role in human communication, automatic emotion recognition has attracted increasing attention in the last two decades. While multimodal systems enjoy hig…
An Audio-Video Deep and Transfer Learning Framework for Multimodal Emotion Recognition in the wild
Denis Dresvyanskiy, Elena Ryumina, Heysem Kaya +3
In this paper, we present our contribution to ABAW facial expression challenge. We report the proposed system and the official challenge results adhering to the challenge protocol.…
Detecting anomalies in fibre systems using 3-dimensional image data
Denis Dresvyanskiy, Tatiana Karaseva, Vitalii Makogin +3
We consider the problem of detecting anomalies in the directional distribution of fibre materials observed in 3D images. We divide the image into a set of scanning windows and clas…
Application of Clustering Methods to Anomaly Detection in Fibrous Media
Denis Dresvyanskiy, Tatiana Karaseva, Sergei Mitrofanov +4
The paper considers the problem of anomaly detection in 3D images of fibre materials. The spatial Stochastic Expectation Maximisation algorithm and Adaptive Weights Clustering are…