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
February 27, 2021
Understanding Training Efficiency of Deep Learning Recommendation Models at Scale
The use of GPUs has proliferated for machine learning workflows and is now considered mainstream for many deep learning models…
Bilge Acun, Matthew Murphy, Xiaodong Wang, Jade Nie, Carole-Jean Wu, Kim Hazelwood
February 27, 2021
February 01, 2021
RANKING & RECOMMENDATIONS
Anytime Inference with Distilled Hierarchical Neural Ensembles
Inference in deep neural networks can be computationally expensive, and networks capable of anytime inference are important in scenarios where the amount of compute or quantity of input data varies over time.…
Adria Ruiz, Jakob Verbeek
February 01, 2021
January 09, 2021
COMPUTER VISION
Tarsier: Evolving Noise Injection in Super-Resolution GANs
Super-resolution aims at increasing the resolution and level of detail within an image.…
Baptiste Roziere, Nathanaël Carraz Rakotonirina, Vlad Hosu, Andry Rasoanaivo, Hanhe Lin, Camille Couprie, Olivier Teytaud
January 09, 2021
January 05, 2021
IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL | Facebook AI Research
We propose a novel framework to identify subgoals useful for exploration in sequential decision making tasks under partial observability. We utilize the variational intrinsic control…
Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam
January 05, 2021
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.
