Raghav Kapoor

About

Raghav Kapoor is a researcher at the forefront of human-robot interaction (HRI) and affective computing, with a focused expertise in emotion detection through advanced computer vision and deep learning. His most cited work, "MoEmo Vision Transformer: Integrating Cross-Attention and Movement Vectors in 3D Pose Estimation for HRI Emotion Detection" (2023, 5 citations), introduces a novel framework that addresses critical limitations in traditional emotion recognition systems. By integrating cross-attention mechanisms with movement vectors from 3D pose estimation, Kapoor’s model captures nuanced spatiotemporal interactions often missed by information-constrained datasets and simpler architectures. This contribution enhances the robustness and contextual awareness of emotion detection, enabling more intuitive and responsive human-robot collaboration. His work is particularly notable for bridging the gap between pose dynamics and emotional states, a challenge that has hindered intelligent HRI systems. With a growing citation impact, Kapoor’s research is shaping the next generation of socially aware robots, offering a pathway toward machines that can perceive and adapt to human emotional cues in real-time.

Research Focus

Key Achievements

Top Papers

1. 1
   MoEmo Vision Transformer: Integrating Cross-Attention and Movement Vectors in 3D Pose Estimation for HRI Emotion Detection

   5 citations · 2023

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