Bringing the world closer together by advancing AI

DensePose

Bringing the world closer together by advancing AI

GrokNet

Bringing the world closer together by advancing AI

Deepfake Detection

Bringing the world closer together by advancing AI

DensePose

Bringing the world closer together by advancing AI

GrokNet

Bringing the world closer together by advancing AI

Deepfake Detection

Open-Source AI Tools

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.

Open-Source AI Research

We're advancing the state-of-the-art in artificial intelligence through fundamental and applied research in open collaboration with the community.

Notable Papers

RESEARCH

ML APPLICATIONS

GrokNet: Unified Computer Vision Model Trunk and Embeddings For Commerce

Sean Bell

Yiqun Liu

Sami Alsheikh

Yina Tang...

KDD

COMPUTER VISION

Live Face De-Identification in Video

Oran Gafni

Lior Wolf

Yaniv Taigman

International Conference on Computer Vision (ICCV)

RESEARCH

Single-Network Whole-Body Pose Estimation

Gines Hidalgo

Yaadhav Raaj

Haroon Idrees

Donglai Xiang...

International Conference on Computer Vision (ICCV)

SPEECH & AUDIO

A Universal Music Translation Network

Noam Mor

Lior Wolf

Adam Polyak

Yaniv Taigman

International Conference on Learning Representations (ICLR)

Latest Publications

NLP

Support-Set bottlenecks for video-text representation learning

The dominant paradigm for learning video-text representations -- noise contrastive learning -- increases the similarity of the representations of pairs of samples

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

RESPONSIBLE AI

INTEGRITY

Towards measuring fairness in AI: the Casual Conversations dataset

This paper introduces a novel dataset to help researchers evaluate their computer vision and audio models for accuracy across a diverse set of age, genders, apparent skin tones and ambient lighting conditions

Caner Hazirbas, Joanna Bitton,Brian Dolhansky, Jacqueline Pan, Albert Gordo, Cristian Canton Ferrer

CORE MACHINE LEARNING

COMPUTER VISION

Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs

A wide variety of deep learning techniques from style transfer to multitask learning rely on training affine transformations of features …

Jonathan Frankle, David J. Schwab, Ari S Morcos

NLP

MixKD: Towards Efficient Distillation of Large-scale Language Models

Large-scale language models have recently demonstrated impressive empirical performance. Nevertheless, the improved results are attained at the price of bigger models …

Kevin J Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin

Help Us Pioneer the Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.