92 citations · 203 across the 7 of their papers we have counts for
7 papers
TLDR: Twin Learning for Dimensionality Reduction
Yannis Kalantidis, Carlos Lassance, Jon Almazan +1
Dimensionality reduction methods are unsupervised approaches which learn low-dimensional spaces where some properties of the initial space, typically the notion of "neighborhood",…
Learning with Average Precision: Training Image Retrieval with a Listwise Loss
Jerome Revaud, Jon Almazan, Rafael Sampaio de Rezende +1
Image retrieval can be formulated as a ranking problem where the goal is to order database images by decreasing similarity to the query. Recent deep models for image retrieval have…
Re-ID done right: towards good practices for person re-identification
Jon Almazan, Bojana Gajic, Naila Murray +1
Training a deep architecture using a ranking loss has become standard for the person re-identification task. Increasingly, these deep architectures include additional components th…
End-to-end Learning of Deep Visual Representations for Image Retrieval
Albert Gordo, Jon Almazan, Jerome Revaud +1
While deep learning has become a key ingredient in the top performing methods for many computer vision tasks, it has failed so far to bring similar improvements to instance-level i…
Deep Image Retrieval: Learning global representations for image search
Albert Gordo, Jon Almazan, Jerome Revaud +1
We propose a novel approach for instance-level image retrieval. It produces a global and compact fixed-length representation for each image by aggregating many region-wise descript…
What is the right way to represent document images?
Gabriela Csurka, Diane Larlus, Albert Gordo +1
In this article we study the problem of document image representation based on visual features. We propose a comprehensive experimental study that compares three types of visual do…
LEWIS: Latent Embeddings for Word Images and their Semantics
Albert Gordo, Jon Almazan, Naila Murray +1
The goal of this work is to bring semantics into the tasks of text recognition and retrieval in natural images. Although text recognition and retrieval have received a lot of atten…