Search Results for author: Filip Radenovic

Found 11 papers, 4 papers with code

Large-Scale Attribute-Object Compositions

no code implementations24 May 2021 Filip Radenovic, Animesh Sinha, Albert Gordo, Tamara Berg, Dhruv Mahajan

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.

Attention-Based Query Expansion Learning

no code implementations ECCV 2020 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, generally leading to increased recall and precision.

Image Retrieval

Targeted Mismatch Adversarial Attack: Query with a Flower to Retrieve the Tower

1 code implementation ICCV 2019 Giorgos Tolias, Filip Radenovic, Ondřej Chum

We show successful attacks to partially unknown systems, by designing various loss functions for the adversarial image construction.

Adversarial Attack

Camera Elevation Estimation from a Single Mountain Landscape Photograph

no code implementations12 Jul 2016 Martin Cadik, Jan Vasicek, Michal Hradis, Filip Radenovic, Ondrej Chum

This work addresses the problem of camera elevation estimation from a single photograph in an outdoor environment.

From Dusk Till Dawn: Modeling in the Dark

no code implementations CVPR 2016 Filip Radenovic, Johannes L. Schonberger, Dinghuang Ji, Jan-Michael Frahm, Ondrej Chum, Jiri Matas

We present an algorithm that leverages the appearance variety to obtain more complete and accurate scene geometry along with consistent multi-illumination appearance information.

Multiple Measurements and Joint Dimensionality Reduction for Large Scale Image Search with Short Vectors - Extended Version

no code implementations13 Apr 2015 Filip Radenovic, Herve Jegou, Ondrej Chum

This paper addresses the construction of a short-vector (128D) image representation for large-scale image and particular object retrieval.

Dimensionality Reduction Image Retrieval

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