2 citations · 6 across the 10 of their papers we have counts for
10 papers
AffectGPT-RL: Revealing Roles of Reinforcement Learning in Open-Vocabulary Emotion Recognition
Zheng Lian, Fan Zhang, Lan Chen +8
Open-Vocabulary Multimodal Emotion Recognition (OV-MER) aims to predict emotions without being constrained by predefined label spaces, thereby enabling fine-grained emotion underst…
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…
Machine Learning-Based Classification of Jhana Advanced Concentrative Absorption Meditation Using 7 Tesla Functional Magnetic Resonance Imaging
Puneet Kumar, Winson F. Z. Yang, Alakhsimar Singh +2
Introduction: Jhana advanced concentrative absorption meditation (ACAM-J) involves profound changes in consciousness, making its neural correlates important for understanding consc…
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…
AffectGPT-R1: Leveraging Reinforcement Learning for Open-Vocabulary Multimodal Emotion Recognition
Zheng Lian, Fan Zhang, Yazhou Zhang +5
Open-Vocabulary Multimodal Emotion Recognition (OV-MER) aims to predict emotions without being constrained by label spaces, enabling fine-grained emotion understanding. Unlike trad…
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…
Computational Analysis of Stress, Depression and Engagement in Mental Health: A Survey
Puneet Kumar, Alexander Vedernikov, Yuwei Chen +2
Analysis of stress, depression and engagement is less common and more complex than that of frequently discussed emotions such as happiness, sadness, fear and anger. The importance…
Synthesizing Sentiment-Controlled Feedback For Multimodal Text and Image Data
Puneet Kumar, Sarthak Malik, Balasubramanian Raman +1
The ability to generate sentiment-controlled feedback in response to multimodal inputs comprising text and images addresses a critical gap in human-computer interaction. This capab…
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…