RESEARCH

ML APPLICATIONS

GrokNet: Unified Computer Vision Model Trunk and Embeddings For Commerce

August 22, 2020

Abstract

In this paper, we present GrokNet, a deployed image recognition system for commerce applications. GrokNet leverages a multi-task learning approach to train a single computer vision trunk. We achieve a 2.1x improvement in exact product match accuracy when compared to the previous state-of-the-art Facebook product recognition system. We achieve this by training on 7 datasets across several commerce verticals, using 80 categorical loss functions and 3 embedding losses. We share our experience of combining diverse sources with wide-ranging label semantics and image statistics, including learning from human annotations, user-generated tags, and noisy search engine interaction data. GrokNet has demonstrated gains in production applications and operates at Facebook scale.

Download the Paper

AUTHORS

Written by

Sean Bell

Yiqun Liu

Sami Alsheikh

Yina Tang

Ed Pizzi

M. Henning

Karun Singh

Omkar Parkhi

Fedor Borisyuk

Publisher

KDD

Recent Publications

May 14, 2021

Not All Memories are Created Equal: Learning to Forget by Expiring

Sainbayar Sukhbaatar, Da Ju, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, Angela Fan

May 14, 2021

May 03, 2021

NLP

Support-Set bottlenecks for video-text representation learning

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

May 03, 2021

April 08, 2021

RESPONSIBLE AI

INTEGRITY

Towards measuring fairness in AI: the Casual Conversations dataset

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

April 08, 2021

March 13, 2021

REINFORCEMENT LEARNING

On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning

Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, Andre Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra

March 13, 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.