Lorenzo Torresani

Research Scientist

I am a research scientist at Facebook AI Research (FAIR) and Applied Machine Learning (AML). I am also an associate professor in the Computer Science Department at Dartmouth.
I received a Laurea Degree in computer science with summa cum laude honors from the University of Milan (Italy) in 1996, and an MS and a PhD in computer science from Stanford University in 2001 and 2005, respectively. Prior to Facebook, I have worked at several other industrial research labs, including Microsoft Research, and Digital Persona. My research interests are in computer vision and deep learning. I am the recipient of a CVPR best student paper prize, a National Science Foundation CAREER Award, a Google Faculty Research Award, three Facebook Faculty Awards and a Fulbright US Scholar Award.


Computer vision, deep learning and artificial intelligence

Latest Publications

NeurIPS - December 6, 2020

Self-Supervised Learning by Cross-Modal Audio-Video Clustering

Humam Alwassel, Dhruv Mahajan, Bruno Korbar, Lorenzo Torresani, Bernard Ghanem, Du Tran

CVPR - June 14, 2020

Listen to Look: Action Recognition by Previewing Audio

Ruohan Gao, Tae-Hyun Oh, Kristen Grauman, Lorenzo Torresani

CVPR - June 14, 2020

Video Modeling with Correlation Networks

Heng Wang, Du Tran, Lorenzo Torresani, Matt Feiszli

ICCV - October 27, 2019

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

NeurIPS - October 27, 2019

Learning Temporal Pose Estimation from Sparsely-Labeled Videos

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

CVPR Precognition Workshop - June 16, 2019

Leveraging the Present to Anticipate the Future in Videos

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

BMVC 2018 - September 4, 2018

Self-Supervised Feature Learning for Semantic Segmentation of Overhead Imagery

Suriya Singh, Anil Batra, Guan Pang, Lorenzo Torresani, Saikat Basu, Manohar Paluri, C.V. Jawahar

CVPR 2018 - June 18, 2018

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

What Makes a Video a Video: Analyzing Temporal Information in Video Understanding Models and Datasets

De-An Huang, Vignesh Ramanathan, Dhruv Mahajan, Lorenzo Torresani, Manohar Paluri, Li Fei-Fei, Juan Carlos Niebles

CVPR 2016 - June 26, 2016

End-to-End Voxel-to-Voxel Prediction

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

ArXiv - June 22, 2015

Learning Spatiotemporal Features with 3D Convolutional Networks

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