Papers
3
Total Citations
206
H-Index
3
About
Abhinav Dhall is a leading researcher in computer vision and affective computing, with a focus on emotion recognition, human behavior analysis, and image enhancement. He is best known for pioneering work in real-world emotion recognition, having co-organized the first EmotiW challenge in 2013, which catalyzed a shift from lab-controlled studies to robust, in-the-wild facial expression analysis. Dhall’s contributions extend to generative AI and human-robot interaction; his BEAMER framework (2023) models appropriate listener facial reactions during dyadic conversations, advancing socially-aware avatars. His highly cited work on UW-GAN (2021, 192 citations) tackles the challenging problem of single-image depth estimation and enhancement for underwater scenes, demonstrating his versatility across domains. Through these efforts, Dhall has significantly impacted both applied computer vision and the development of emotionally intelligent systems, shaping how machines perceive and respond to human cues in complex, unconstrained environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2BEAMER: Behavioral Encoder to Generate Multiple Appropriate Facial Reactions11 citations · 2023
- 3