activity
20172021
most citedRosetta: Large scale system for text detection and recognition in images

338 citations · 603 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV20214 cited

Large-Scale Attribute-Object Compositions

Filip Radenovic, Animesh Sinha, Albert Gordo +2

We study the problem of learning how to predict attribute-object compositions from images, and its generalization to unseen compositions missing from the training data. To the best…

cs.CV2021

Towards Measuring Fairness in AI: the Casual Conversations Dataset

Caner Hazirbas, Joanna Bitton, Brian Dolhansky +3

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…

cs.CV2020

Attention-Based Query Expansion Learning

Albert Gordo, Filip Radenovic, Tamara Berg

Query expansion is a technique widely used in image search consisting in combining highly ranked images from an original query into an expanded query that is then reissued, general…

cs.LG2020

Using Hindsight to Anchor Past Knowledge in Continual Learning

Arslan Chaudhry, Albert Gordo, Puneet K. Dokania +2

In continual learning, the learner faces a stream of data whose distribution changes over time. Modern neural networks are known to suffer under this setting, as they quickly forge…

cs.CV2019338 cited

Rosetta: Large scale system for text detection and recognition in images

Fedor Borisyuk, Albert Gordo, Viswanath Sivakumar

In this paper we present a deployed, scalable optical character recognition (OCR) system, which we call Rosetta, designed to process images uploaded daily at Facebook scale. Sharin…

cs.CV2019219 cited

Decoupling Representation and Classifier for Long-Tailed Recognition

Bingyi Kang, Saining Xie, Marcus Rohrbach +4

The long-tail distribution of the visual world poses great challenges for deep learning based classification models on how to handle the class imbalance problem. Existing solutions…