102 citations · 191 across the 15 of their papers we have counts for
17 papers
Naturalistic Head Motion Generation from Speech
Trisha Mittal, Zakaria Aldeneh, Masha Fedzechkina +2
Synthesizing natural head motion to accompany speech for an embodied conversational agent is necessary for providing a rich interactive experience. Most prior works assess the qual…
Estimating Emotion Contagion on Social Media via Localized Diffusion in Dynamic Graphs
Trisha Mittal, Puneet Mathur, Rohan Chandra +5
We present a computational approach for estimating emotion contagion on social media networks. Built on a foundation of psychology literature, our approach estimates the degree to…
Video Manipulations Beyond Faces: A Dataset with Human-Machine Analysis
Trisha Mittal, Ritwik Sinha, Viswanathan Swaminathan +2
As tools for content editing mature, and artificial intelligence (AI) based algorithms for synthesizing media grow, the presence of manipulated content across online media is incre…
3MASSIV: Multilingual, Multimodal and Multi-Aspect dataset of Social Media Short Videos
Vikram Gupta, Trisha Mittal, Puneet Mathur +5
We present 3MASSIV, a multilingual, multimodal and multi-aspect, expertly-annotated dataset of diverse short videos extracted from short-video social media platform - Moj. 3MASSIV…
Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causality
Trisha Mittal, Puneet Mathur, Aniket Bera +1
We present Affect2MM, a learning method for time-series emotion prediction for multimedia content. Our goal is to automatically capture the varying emotions depicted by characters…
Dynamic Graph Modeling of Simultaneous EEG and Eye-tracking Data for Reading Task Identification
Puneet Mathur, Trisha Mittal, Dinesh Manocha
We present a new approach, that we call AdaGTCN, for identifying human reader intent from Electroencephalogram~(EEG) and Eye movement~(EM) data in order to help differentiate betwe…
Generating Emotive Gaits for Virtual Agents Using Affect-Based Autoregression
Uttaran Bhattacharya, Nicholas Rewkowski, Pooja Guhan +4
We present a novel autoregression network to generate virtual agents that convey various emotions through their walking styles or gaits. Given the 3D pose sequences of a gait, our…
MCQA: Multimodal Co-attention Based Network for Question Answering
Abhishek Kumar, Trisha Mittal, Dinesh Manocha
We present MCQA, a learning-based algorithm for multimodal question answering. MCQA explicitly fuses and aligns the multimodal input (i.e. text, audio, and video), which forms the…
EmotiCon: Context-Aware Multimodal Emotion Recognition using Frege's Principle
Trisha Mittal, Pooja Guhan, Uttaran Bhattacharya +3
We present EmotiCon, a learning-based algorithm for context-aware perceived human emotion recognition from videos and images. Motivated by Frege's Context Principle from psychology…
Emotions Don't Lie: An Audio-Visual Deepfake Detection Method Using Affective Cues
Trisha Mittal, Uttaran Bhattacharya, Rohan Chandra +2
We present a learning-based method for detecting real and fake deepfake multimedia content. To maximize information for learning, we extract and analyze the similarity between the…
CMetric: A Driving Behavior Measure Using Centrality Functions
Rohan Chandra, Uttaran Bhattacharya, Trisha Mittal +2
We present a new measure, CMetric, to classify driver behaviors using centrality functions. Our formulation combines concepts from computational graph theory and social traffic psy…
Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs
Rohan Chandra, Tianrui Guan, Srujan Panuganti +4
We present a novel approach for traffic forecasting in urban traffic scenarios using a combination of spectral graph analysis and deep learning. We predict both the low-level infor…
M3ER: Multiplicative Multimodal Emotion Recognition Using Facial, Textual, and Speech Cues
Trisha Mittal, Uttaran Bhattacharya, Rohan Chandra +2
We present M3ER, a learning-based method for emotion recognition from multiple input modalities. Our approach combines cues from multiple co-occurring modalities (such as face, tex…
Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping
Uttaran Bhattacharya, Christian Roncal, Trisha Mittal +5
We present an autoencoder-based semi-supervised approach to classify perceived human emotions from walking styles obtained from videos or motion-captured data and represented as se…
STEP: Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits
Uttaran Bhattacharya, Trisha Mittal, Rohan Chandra +3
We present a novel classifier network called STEP, to classify perceived human emotion from gaits, based on a Spatial Temporal Graph Convolutional Network (ST-GCN) architecture. Gi…
GraphRQI: Classifying Driver Behaviors Using Graph Spectrums
Rohan Chandra, Uttaran Bhattacharya, Trisha Mittal +3
We present a novel algorithm (GraphRQI) to identify driver behaviors from road-agent trajectories. Our approach assumes that the road-agents exhibit a range of driving traits, such…
Game of Sketches: Deep Recurrent Models of Pictionary-style Word Guessing
Ravi Kiran Sarvadevabhatla, Shiv Surya, Trisha Mittal +1
The ability of intelligent agents to play games in human-like fashion is popularly considered a benchmark of progress in Artificial Intelligence. Similarly, performance on multi-di…