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20182022
most citedSTEP: Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

102 citations · 191 across the 15 of their papers we have counts for

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8 papers · 1 filter

cs.CV2022

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…

cs.CV2022★ 1 cited

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…

cs.CV2021

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…

cs.CV2020★ 2 cited

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…

cs.CV2020★ 13 cited

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…

cs.CV2019★ 44 cited

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…

cs.CV2019★ 102 cited

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…

cs.CV2018

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…