Our new oral at ICCV’19 now has a presentation & video:
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
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
Unsupervised Visual Domain Adaptation:A Deep Max-Margin Gaussian Process Approach : Oral Paper at CVPR 2019
This is a joint work by Minyoung Kim, Pritish Sahu, Behnam Gholami, Vladimir Pavlovic.
Abstract
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
New AAAI’18 paper on Crowd Modeling
Our paper “The Role of Data Driven Priors in Multi-agent Crowd Trajectory Estimation” has been accepted to AAAI’18.
Congratulations to Gang on his hard work!… Read the rest
ICCV 2017 – Wrap Up
Last week was the time for ICCV 2017 in Venice, Italy. Setting aside my personal indifference to Venice (overcrowded and overpriced, uninspiring food), ICCV was an interesting meeting. It took place on Lido, at the same venue as the Venice … Read the rest
“Unsupervised Domain Adaptation with Copula Models” presented at MLSP’17
Our paper “Unsupervised Domain Adaptation with Copula Models”[1] was presented this week at the IEEE Int’l Workshop on Machine Learning for Signal Processing in Tokyo, Japan.
It was an exciting meeting; unlike the now mega-conferences of CVPR and … Read the rest
CVPR 2017 – Wrap Up
It was quite exciting to attend the largest CVPR ever – almost 5000 attendees. Having it in a beautiful location made it even more appealing.
Thanks to my students and colleagues who made the work we presented at CVPR possible.… Read the rest
ICCV 2017
Our paper about unsupervised probabilistic domain adaptation [1] for deep models (and other models too) has been accepted for ICCV’17:
[1] B. Gholami, O. Rudovic, and V. Pavlovic, “PUnDA: Probabilistic Unsupervised Domain Adaptation,” in Proc. IEEE International Conference
… Read the rest CVPR 2017
We are excited to have three CVPR 2017 main conference papers accepted [1, 2, 3], as well as one workshop paper [4] :
[1] B. Babagholami and V. Pavlovic, “Probabilistic Temporal Subspace Clustering,” in
… Read the rest