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
Hai X. Pham, Yuting Wang & Vladimir Pavlovic.
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
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.
We present a deep learning framework for real-time speech-driven 3D facial animation … Read the rest
Our new paper on crowd simulation was accepted by ACM SIGGRAPH Conference on Motion, Interaction and Games 2019. Congratulations to Gang!
Crowd simulation, the study of the movement of multiple agents in complex environments, presents a unique application domain for … Read the rest
Our new paper on Bayesian representation learning was accepted as Oral at ICCV 2019. Congratulations to Minyoung, Yuting, and Pritish!
We propose a family of novel hierarchical Bayesian deep auto-encoder models capable of identifying disentangled factors of variability in … Read the rest
In this work we propose a new computational framework, based on generative deep models, for synthesis of photo-realistic food meal images from textual … Read the rest
This is a joint work by Minyoung Kim, Pritish Sahu, Behnam Gholami, Vladimir Pavlovic.
For unsupervised domain adaptation, the target domain error can be provably reduced by having a shared input representation that makes the source and target domains … Read the rest
If you are interested in registering for my Fall 2018 cs535 Pattern Recognition and do not have the prerequisites or for some other reason need a Special Permission (SPN) or Prerequisite Override, you will need to fill out a request … Read the rest
Our paper “The Role of Data Driven Priors in Multi-agent Crowd Trajectory Estimation” has been accepted to AAAI’18.
We recently received some exceptionally encouraging news: Rutgers CS is ranked #9 in the US in the combined categories of Computer Vision / Machine Learning and Data Mining / Information Retrieval.
This is quite an accomplishment. Congratulations to all!… Read the rest