51 citations · 111 across the 11 of their papers we have counts for
6 papers · 1 filter
Learning Stylized Character Expressions from Humans
Deepali Aneja, Alex Colburn, Gary Faigin +2
We present DeepExpr, a novel expression transfer system from humans to multiple stylized characters via deep learning. We developed : 1) a data-driven perceptual model of facial ex…
Real-Time Lip Sync for Live 2D Animation
Deepali Aneja, Wilmot Li
The emergence of commercial tools for real-time performance-based 2D animation has enabled 2D characters to appear on live broadcasts and streaming platforms. A key requirement for…
Designing Style Matching Conversational Agents
Deepali Aneja, Rens Hoegen, Daniel McDuff +1
Advances in machine intelligence have enabled conversational interfaces that have the potential to radically change the way humans interact with machines. However, even with the pr…
A High-Fidelity Open Embodied Avatar with Lip Syncing and Expression Capabilities
Deepali Aneja, Daniel McDuff, Shital Shah
Embodied avatars as virtual agents have many applications and provide benefits over disembodied agents, allowing non-verbal social and interactional cues to be leveraged, in a simi…
A Facial Affect Analysis System for Autism Spectrum Disorder
Beibin Li, Sachin Mehta, Deepali Aneja +4
In this paper, we introduce an end-to-end machine learning-based system for classifying autism spectrum disorder (ASD) using facial attributes such as expressions, action units, ar…
An End-to-End Conversational Style Matching Agent
Rens Hoegen, Deepali Aneja, Daniel McDuff +1
We present an end-to-end voice-based conversational agent that is able to engage in naturalistic multi-turn dialogue and align with the interlocutor's conversational style. The sys…