Search Results for author: Filip Radenović

Found 4 papers, 4 papers with code

Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking

2 code implementations CVPR 2018 Filip Radenović, Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, Ondřej Chum

In particular, annotation errors, the size of the dataset, and the level of challenge are addressed: new annotation for both datasets is created with an extra attention to the reliability of the ground truth.

Image Retrieval

Fine-tuning CNN Image Retrieval with No Human Annotation

13 code implementations3 Nov 2017 Filip Radenović, Giorgos Tolias, Ondřej Chum

We show that both hard-positive and hard-negative examples, selected by exploiting the geometry and the camera positions available from the 3D models, enhance the performance of particular-object retrieval.

Image Retrieval

CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples

5 code implementations8 Apr 2016 Filip Radenović, Giorgos Tolias, Ondřej Chum

Convolutional Neural Networks (CNNs) achieve state-of-the-art performance in many computer vision tasks.

Image Retrieval

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