Shrinidhi Kowshika Lakshmikanth

ViBES: A Conversational Agent with Behaviorally-Intelligent 3D Virtual Body

Juze Zhang, Changan Chen, Xin Chen, Heng Yu et autres

Human communication is inherently multimodal and social: words, prosody, and body language jointly carry intent. Yet most prior systems model human behavior as a translation task co-speech gesture or text-to-motion that maps a fixed utterance to motion clips-without requiring agentic decision-making about …

An Interactive Agent Foundation Model

Zane Durante, Ran Gong, Bidipta Sarkar, Noaki Wake et autres

The development of artificial intelligence systems is transitioning from creating static, task-specific models to dynamic, agent-based systems capable of performing well in a wide range of applications. We propose an Interactive Agent Foundation Model that uses a novel multi-task agent training paradigm …

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The Language of Motion: Unifying Verbal and Non-verbal Language of 3D Human Motion

Changan Chen, Juze Zhang, Shrinidhi Kowshika Lakshmikanth, Yue Fang et autres

Human communication is inherently multimodal, involving a combination of verbal and non-verbal cues such as speech, facial expressions, and body gestures. Modeling these behaviors is essential for understanding human interaction and for creating virtual characters that can communicate naturally in applications like …

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Developing ICU Clinical Behavioral Atlas Using Ambient Intelligence and Computer Vision

Ehsan Adeli, Zelun Luo, Dev Dash, Shrinidhi Kowshika Lakshmikanth et autres

BACKGROUND: While computer vision has gained traction in medical applications, models specifically engineered for intensive care unit (ICU) activities are limited. METHODS: We present Clinical Behavioral Atlas (CBA), a computer vision system that can identify 40 clinically relevant activity categories and 55 …

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The Language of Motion: Unifying Verbal and Non-verbal Language of 3D Human Motion

Changan Chen, Juze Zhang, Shrinidhi Kowshika Lakshmikanth, Ruizhi Shao et autres

Human communication is inherently multimodal, involving a combination of verbal and non-verbal cues such as speech, facial expressions, and body gestures. Modeling these behaviors is essential for understanding human interaction and for creating virtual characters that can communicate naturally in applications like …

An Interactive Agent Foundation Model

Zane Durante, Bidipta Sarkar, Ran Gong, Rohan Taori et autres

The development of artificial intelligence systems is transitioning from creating static, task-specific models to dynamic, agent-based systems capable of performing well in a wide range of applications. We propose an Interactive Agent Foundation Model that uses a novel multi-task agent training paradigm …

Characterizing Geographic Variation in Well-Being Using Tweets

Hansen Andrew Schwartz, Johannes C. Eichstaedt, Margaret L. Kern, Lukasz Dziurzynski et autres

The language used in tweets from 1,300 different US counties was found to be predictive of the subjective well-being of people living in those counties as measured by representative surveys. Topics, sets of co-occurring words derived from the tweets using LDA, improved …

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Hierarchical Recurrent Attention Networks for Structured Online Maps

Namdar Homayounfar, Wei-Chiu Ma, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun

In this paper, we tackle the problem of online road network extraction from sparse 3D point clouds. Our method is inspired by how an annotator builds a lane graph, by first identifying how many lanes there are and then drawing each one …

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Not Just Semantics: Social Distancing and COVID Discourse on Twitter

Austin van Loon, Sheridan A. Stewart, Brandon Waldon, Shrinidhi Kowshika Lakshmikanth et autres

Tracking Emerges by Looking Around Static Scenes, with Neural 3D Mapping

Adam W. Harley, Shrinidhi Kowshika Lakshmikanth, Paul Schydlo, Katerina Fragkiadaki

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Explaining the Trump Gap in Social Distancing Using COVID Discourse

Austin van Loon, Sheridan A. Stewart, Brandon Waldon, Shrinidhi Kowshika Lakshmikanth et autres

Austin Van Loon, Sheridan Stewart, Brandon Waldon, Shrinidhi K Lakshmikanth, Ishan Shah, Sharath Chandra Guntuku, Garrick Sherman, James Zou, Johannes Eichstaedt. Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020. 2020.

Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization

Wei-Chiu Ma, Ignacio Tartavull, Ioan Andrei Bârsan, Shenlong Wang et autres

In this paper we propose a novel semantic localization algorithm that exploits multiple sensors and has precision on the order of a few centimeters. Our approach does not require detailed knowledge about the appearance of the world, and our maps require orders …

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