Search Results for author: Joaquin Zepeda

Found 7 papers, 1 papers with code

Learning a Complete Image Indexing Pipeline

no code implementations CVPR 2018 Himalaya Jain, Joaquin Zepeda, Patrick Pérez, Rémi Gribonval

To work at scale, a complete image indexing system comprises two components: An inverted file index to restrict the actual search to only a subset that should contain most of the items relevant to the query; An approximate distance computation mechanism to rapidly scan these lists.


Kernel Square-Loss Exemplar Machines for Image Retrieval

no code implementations CVPR 2017 Rafael S. Rezende, Joaquin Zepeda, Jean Ponce, Francis Bach, Patrick Perez

Zepeda and Perez have recently demonstrated the promise of the exemplar SVM (ESVM) as a feature encoder for image retrieval.

Image Retrieval Retrieval

Approximate search with quantized sparse representations

no code implementations10 Aug 2016 Himalaya Jain, Patrick Pérez, Rémi Gribonval, Joaquin Zepeda, Hervé Jégou

This paper tackles the task of storing a large collection of vectors, such as visual descriptors, and of searching in it.


Exemplar SVMs as Visual Feature Encoders

no code implementations CVPR 2015 Joaquin Zepeda, Patrick Perez

In this work, we investigate the use of exemplar SVMs (linear SVMs trained with one positive example only and a vast collection of negative examples) as encoders that turn generic image features into new, task-tailored features.

Image Classification Image Retrieval +1

Hybrid multi-layer Deep CNN/Aggregator feature for image classification

no code implementations13 Mar 2015 Praveen Kulkarni, Joaquin Zepeda, Frederic Jurie, Patrick Perez, Louis Chevallier

A second variant of our approach that includes the fully connected DCNN layers significantly outperforms Fisher vector schemes and performs comparably to DCNN approaches adapted to Pascal VOC 2007, yet at only a small fraction of the training and testing cost.

Classification General Classification +1

Cannot find the paper you are looking for? You can Submit a new open access paper.