Research Areas

Giving people the power to share and connect requires constant innovation

At Facebook, research permeates everything we do. We believe the most interesting research questions are derived from real world problems. Working on cutting edge research with a practical focus, we push product boundaries every day. At the same time, we publish papers, give talks, and collaborate broadly with the academic community.

We solve real-world problems that impact billions of people in areas such as:

Latest Publications

All Publications

International Conference on Very Large Data Bases (VLDB) - July 31, 2021

CALYPSO: Private Data Management for Decentralized Ledgers

Eleftherios Kokoris-Kogias, Enis Ceyhun Alp, Linus Gasser, Philipp Jovanovic, Ewa Syta, Bryan Ford

CVPR - June 19, 2021

Pixel Codec Avatars

Shugao Ma, Tomas Simon, Jason Saragih, Dawei Wang, Yuecheng Li, Fernando De la Torre, Yaser Sheikh

CVPR - June 19, 2021

SimPoE: Simulated Character Control for 3D Human Pose Estimation

Ye Yuan, Shih-En Wei, Tomas Simon, Kris Kitani, Jason Saragih

ICASSP - June 6, 2021

Multi-Channel Speech Enhancement Using Graph Neural Networks

Panagiotis Tzirakis, Anurag Kumar, Jacob Donley

CVPR - June 1, 2021

Semi-supervised Synthesis of High-Resolution Editable Textures for 3D Humans

Bindita Chaudhuri, Nikolaos Sarafianos, Linda Shapiro, Tony Tung

ICLR - May 3, 2021

Support-Set Bottlenecks for Video-Text Representation Learning

Mandela Patrick, Po-Yao Huang, Florian Metze, Andrea Vedaldi, Alexander Hauptmann, Yuki M. Asano, João Henriques

The Web Conference - April 21, 2021

Stochastic bandits for multi-platform budget optimization in online advertising

Vashist Avadhanula, Riccardo Colini Baldeschi, Stefano Leonardi, Karthik Abinav Sankararaman, Okke Schrijvers

AISTATS - April 13, 2021

Multi-armed Bandits with Cost Subsidy

Deeksha Sinha, Karthik Abinav Sankararaman, Abbas Kazerouni, Vashist Avadhanula

Downloads & Projects

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PyTorch is a Python package that provides two high-level features: tensor computation (like NumPy) with strong GPU acceleration and deep neural networks built on a tape-based autograd system.

Dense human pose estimation aims at mapping all human pixels of an RGB image to the 3D surface of the human body.

Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.

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