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Sequence Analysis and Modeling Lab

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Day: September 21, 2019

Posted on September 21, 2019October 2, 2019

Relevance Factor VAE: Learning and Identifying Disentangled Factors

Minyoung Kim, Yuting Wang, Pritish Sahu, and Vladimir Pavlovic.

Abstract

We propose a novel VAE-based deep auto- encoder model that can learn disentangled latent representations in a fully unsupervised manner, endowed with the ability to identify all … Read the rest

Posted on September 21, 2019October 2, 2019

Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network

Hai X. Pham, Yuting Wang & Vladimir Pavlovic.

Abstract

This paper presents Generative Adversarial Talking Head, a novel deep generative neural network that enables fully automatic facial expression synthesis of an arbitrary portrait with continuous action unit (AU) coefficients. … Read the rest

Posted on September 21, 2019October 2, 2019

End-to-end Learning for 3D Facial Animation from Speech, ICMI 2018

This is a joint work by Hai Xuan Pham, Yuting Wang, and Vladimir Pavlovic. The paper was accepted by the 20th ACM International Conference on Multimodal Interaction.

Abstract

We present a deep learning framework for real-time speech-driven 3D facial animation … Read the rest

Posted on September 21, 2019October 2, 2019

Scenario Generalization of Data-driven Imitation Models in Crowd Simulation, MIG2019

Our new paper on crowd simulation was accepted by ACM SIGGRAPH Conference on Motion, Interaction and Games 2019. Congratulations to Gang!

ABSTRACT

Crowd simulation, the study of the movement of multiple agents in complex environments, presents a unique application domain for … Read the rest

Recent Posts

  • Spring 2022 – CS536 – Machine Learning
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  • Picture-to-Amount (PITA): Predicting Relative Ingredient Amounts from Food Images
  • New NSF Grant: Learning Joint Crowd-Space Embeddings for Cross-Modal Crowd Behavior Prediction

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    SEQAM Lab
    CBIM Center
    Rutgers University
    617 Bowser Road
    Piscataway, New Jersey 08854
    United States of America
    Phone: +1 (848) 445-8846
    Fax:  +1 (732) 445-0537

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