Search Results for author: Deepali Aneja

Found 8 papers, 3 papers with code

A Closer Look at the Limitations of Instruction Tuning

no code implementations3 Feb 2024 Sreyan Ghosh, Chandra Kiran Reddy Evuru, Sonal Kumar, Ramaneswaran S, Deepali Aneja, Zeyu Jin, Ramani Duraiswami, Dinesh Manocha

Our findings reveal that responses generated solely from pre-trained knowledge consistently outperform responses by models that learn any form of new knowledge from IT on open-source datasets.

Hallucination

Learning Stylized Character Expressions from Humans

no code implementations19 Nov 2019 Deepali Aneja, Alex Colburn, Gary Faigin, Linda Shapiro, Barbara Mones

We present DeepExpr, a novel expression transfer system from humans to multiple stylized characters via deep learning.

Retrieval

Real-Time Lip Sync for Live 2D Animation

1 code implementation19 Oct 2019 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.

Constrained Lip-synchronization Data Augmentation

Designing Style Matching Conversational Agents

no code implementations16 Oct 2019 Deepali Aneja, Rens Hoegen, Daniel McDuff, Mary Czerwinski

Advances in machine intelligence have enabled conversational interfaces that have the potential to radically change the way humans interact with machines.

valid

A High-Fidelity Open Embodied Avatar with Lip Syncing and Expression Capabilities

1 code implementation19 Sep 2019 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 similar manner to how humans interact with each other.

A Facial Affect Analysis System for Autism Spectrum Disorder

no code implementations7 Apr 2019 Beibin Li, Sachin Mehta, Deepali Aneja, Claire Foster, Pamela Ventola, Frederick Shic, Linda Shapiro

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, arousal, and valence.

BIG-bench Machine Learning Classification +2

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