2 citations · 6 across the 10 of their papers we have counts for
5 papers · 1 filter
GAViD: A Large-Scale Multimodal Dataset for Context-Aware Group Affect Recognition from Videos
Deepak Kumar, Abhishek Pratap Singh, Puneet Kumar +2
Understanding affective dynamics in real-world social systems is fundamental to modeling and analyzing human-human interactions in complex environments. Group affect emerges from i…
Vision Large Language Models Are Good Noise Handlers in Engagement Analysis
Alexander Vedernikov, Puneet Kumar, Haoyu Chen +2
Engagement recognition in video datasets, unlike traditional image classification tasks, is particularly challenged by subjective labels and noise limiting model performance. To ov…
VisioPhysioENet: Visual Physiological Engagement Detection Network
Alakhsimar Singh, Kanav Goyal, Nischay Verma +3
This paper presents VisioPhysioENet, a novel multimodal system that leverages visual and physiological signals to detect learner engagement. It employs a two-level approach for ext…
TCCT-Net: Two-Stream Network Architecture for Fast and Efficient Engagement Estimation via Behavioral Feature Signals
Alexander Vedernikov, Puneet Kumar, Haoyu Chen +2
Engagement analysis finds various applications in healthcare, education, advertisement, services. Deep Neural Networks, used for analysis, possess complex architecture and need lar…
VISTANet: VIsual Spoken Textual Additive Net for Interpretable Multimodal Emotion Recognition
Puneet Kumar, Sarthak Malik, Balasubramanian Raman +1
This paper proposes a multimodal emotion recognition system, VIsual Spoken Textual Additive Net (VISTANet), to classify emotions reflected by input containing image, speech, and te…