15 citations · 19 across the 7 of their papers we have counts for
7 papers
Explainable Depression Detection via Head Motion Patterns
Monika Gahalawat, Raul Fernandez Rojas, Tanaya Guha +2
While depression has been studied via multimodal non-verbal behavioural cues, head motion behaviour has not received much attention as a biomarker. This study demonstrates the util…
Heterogeneous Graph Learning for Acoustic Event Classification
Amir Shirian, Mona Ahmadian, Krishna Somandepalli +1
Heterogeneous graphs provide a compact, efficient, and scalable way to model data involving multiple disparate modalities. This makes modeling audiovisual data using heterogeneous…
Explainable Human-centered Traits from Head Motion and Facial Expression Dynamics
Surbhi Madan, Monika Gahalawat, Tanaya Guha +2
We explore the efficacy of multimodal behavioral cues for explainable prediction of personality and interview-specific traits. We utilize elementary head-motion units named kinemes…
Visually-aware Acoustic Event Detection using Heterogeneous Graphs
Amir Shirian, Krishna Somandepalli, Victor Sanchez +1
Perception of auditory events is inherently multimodal relying on both audio and visual cues. A large number of existing multimodal approaches process each modality using modality-…
Learning Long-Term Spatial-Temporal Graphs for Active Speaker Detection
Kyle Min, Sourya Roy, Subarna Tripathi +2
Active speaker detection (ASD) in videos with multiple speakers is a challenging task as it requires learning effective audiovisual features and spatial-temporal correlations over…
Head Matters: Explainable Human-centered Trait Prediction from Head Motion Dynamics
Surbhi Madan, Monika Gahalawat, Tanaya Guha +1
We demonstrate the utility of elementary head-motion units termed kinemes for behavioral analytics to predict personality and interview traits. Transforming head-motion patterns in…