5 papers · 1 filter
ILIAS: Instance-Level Image retrieval At Scale
Giorgos Kordopatis-Zilos, Vladan Stojnić, Anna Manko +7
This work introduces ILIAS, a new test dataset for Instance-Level Image retrieval At Scale. It is designed to evaluate the ability of current and future foundation models and retri…
Composed Image Retrieval for Training-Free Domain Conversion
Nikos Efthymiadis, Bill Psomas, Zakaria Laskar +4
This work addresses composed image retrieval in the context of domain conversion, where the content of a query image is retrieved in the domain specified by the query text. We show…
Co-Segmentation without any Pixel-level Supervision with Application to Large-Scale Sketch Classification
Nikolaos-Antonios Ypsilantis, Ondřej Chum
This work proposes a novel method for object co-segmentation, i.e. pixel-level localization of a common object in a set of images, that uses no pixel-level supervision for training…
Crafting Distribution Shifts for Validation and Training in Single Source Domain Generalization
Nikos Efthymiadis, Giorgos Tolias, Ondřej Chum
Single-source domain generalization attempts to learn a model on a source domain and deploy it to unseen target domains. Limiting access only to source domain data imposes two key…
Learning and aggregating deep local descriptors for instance-level recognition
Giorgos Tolias, Tomas Jenicek, Ondřej Chum
We propose an efficient method to learn deep local descriptors for instance-level recognition. The training only requires examples of positive and negative image pairs and is perfo…