People

Du Tran

Research Scientist

I am a research scientist at Facebook AI Research (FAIR) and Applied Machine Learning. I graduated with a PhD in computer science from Dartmouth College where I worked with Prof. Lorenzo Torresani. I received an MS in computer science from University of Illinois at Urbana-Champaign where I was advised by Prof. David Forsyth. Before coming to Dartmouth, I was a research staff at Nanyang Technological University working with Prof. Junsong Yuan. My research interests are computer vision, machine learning and computer graphics, with specific interests in video understanding, representation learning, and vision and language. I am a recipient of a Vietnam Education Foundation Fellowship in 2006 and a Dartmouth Presidential Fellowship in 2012.

Interests

Computer vision, machine learning and computer graphics

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Latest Publications

What Makes Training Multi-modal Classification Networks Hard?

Weiyao Wang, Du Tran, Matt Feiszli

CVPR - June 16, 2020

Video Modeling with Correlation Networks

Heng Wang, Du Tran, Lorenzo Torresani, Matt Feiszli

CVPR - June 14, 2020

FASTER Recurrent Networks for Efficient Video Classification

Linchao Zhu, Du Tran, Laura Sevilla-Lara, Yi Yang, Matt Feiszli, Heng Wang

AAAI - February 7, 2020

Video Classification with Channel-Separated Convolutional Networks

Du Tran, Heng Wang, Lorenzo Torresani, Matt Feiszli

ICCV - October 27, 2019

DistInit: Learning Video Representations Without a Single Labeled Video

Rohit Girdhar, Du Tran, Lorenzo Torresani, Deva Ramanan

ICCV - October 27, 2019

SCSampler: Sampling Salient Clips from Video for Efficient Action Recognition

Bruno Korbar, Du Tran, Lorenzo Torresani

ICCV - October 27, 2019

Learning Temporal Pose Estimation from Sparsely-Labeled Videos

Gedas Bertasius, Christoph Feichtenhofer, Du Tran, Jianbo Shi, Lorenzo Torresani

NeurIPS - October 27, 2019

Leveraging the Present to Anticipate the Future in Videos

Antoine Miech, Ivan Laptev, Josef Sivic, Heng Wang, Lorenzo Torresani, Du Tran

CVPR Precognition Workshop - June 16, 2019

Large-scale weakly-supervised pre-training for video action recognition

Deepti Ghadiyaram, Matt Feiszli, Du Tran, Xueting Yan, Hen Wang, Dhruv Mahajan

CVPR - May 1, 2019

A Closer Look at Spatiotemporal Convolutions for Action Recognition

Du Tran, Heng Wang, Lorenzo Torresani, Jamie Ray, Yann LeCun, Manohar Paluri

CVPR 2018 - June 18, 2018

Detect-and-Track: Efficient Pose Estimation in Videos

Rohit Girdhar, Georgia Gkioxari, Lorenzo Torresani, Manohar Paluri, Du Tran

CVPR 2018 - June 18, 2018

End-to-End Voxel-to-Voxel Prediction

Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri

CVPR 2016 - June 26, 2016

Learning Spatiotemporal Features with 3D Convolutional Networks

Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri

ArXiv - June 22, 2015

Latest News

Artificial Intelligence

C3D: Generic Features for Video Analysis

December 8, 2014

Videos

All Videos

What Makes Training Multi-Modal Networks Hard?

| June 10, 2020