Search Results for author: Giorgos Tolias

Found 26 papers, 16 papers with code

Edge Augmentation for Large-Scale Sketch Recognition without Sketches

1 code implementation26 Feb 2022 Nikos Efthymiadis, Giorgos Tolias, Ondrej Chum

To bridge the domain gap we present a novel augmentation technique that is tailored to the task of learning sketch recognition from a training set of natural images.

Edge Detection Sketch Recognition

The Met Dataset: Instance-level Recognition for Artworks

no code implementations3 Feb 2022 Nikolaos-Antonios Ypsilantis, Noa Garcia, Guangxing Han, Sarah Ibrahimi, Nanne van Noord, Giorgos Tolias

Testing is primarily performed on photos taken by museum guests depicting exhibits, which introduces a distribution shift between training and testing.

Contrastive Learning Out-of-Distribution Detection

Recall@k Surrogate Loss with Large Batches and Similarity Mixup

2 code implementations25 Aug 2021 Yash Patel, Giorgos Tolias, Jiri Matas

This work focuses on learning deep visual representation models for retrieval by exploring the interplay between a new loss function, the batch size, and a new regularization approach.

Image Retrieval Metric Learning +1

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

Label Propagation for Deep Semi-supervised Learning

1 code implementation CVPR 2019 Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, Ondrej Chum

In this work, we employ a transductive label propagation method that is based on the manifold assumption to make predictions on the entire dataset and use these predictions to generate pseudo-labels for the unlabeled data and train a deep neural network.

Understanding and Improving Kernel Local Descriptors

3 code implementations27 Nov 2018 Arun Mukundan, Giorgos Tolias, Andrei Bursuc, Hervé Jégou, Ondřej Chum

We propose a multiple-kernel local-patch descriptor based on efficient match kernels from pixel gradients.

Hybrid Diffusion: Spectral-Temporal Graph Filtering for Manifold Ranking

no code implementations23 Jul 2018 Ahmet Iscen, Yannis Avrithis, Giorgos Tolias, Teddy Furon, Ondrej Chum

State of the art image retrieval performance is achieved with CNN features and manifold ranking using a k-NN similarity graph that is pre-computed off-line.

Image Retrieval

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

Mining on Manifolds: Metric Learning without Labels

1 code implementation CVPR 2018 Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, Ondrej Chum

Positive examples are distant points on a single manifold, while negative examples are nearby points on different manifolds.

General Classification Metric Learning

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

Unsupervised object discovery for instance recognition

no code implementations14 Sep 2017 Oriane Siméoni, Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, Ondrej Chum

Eliminating the impact of the clutter on the image descriptor increases the chance of retrieving relevant images and prevents topic drift due to actually retrieving the clutter in the case of query expansion.

Image Retrieval Object Discovery

Multiple-Kernel Local-Patch Descriptor

no code implementations25 Jul 2017 Arun Mukundan, Giorgos Tolias, Ondrej Chum

We propose a multiple-kernel local-patch descriptor based on efficient match kernels of patch gradients.

Panorama to panorama matching for location recognition

no code implementations21 Apr 2017 Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, Teddy Furon, Ondrej Chum

Location recognition is commonly treated as visual instance retrieval on "street view" imagery.

Asymmetric Feature Maps with Application to Sketch Based Retrieval

no code implementations CVPR 2017 Giorgos Tolias, Ondřej Chum

To demonstrate the advantages of the AFM method, we derive a short vector image representation that, due to asymmetric feature maps, supports efficient scale and translation invariant sketch-based image retrieval.

Sketch-Based Image Retrieval Translation

Efficient Diffusion on Region Manifolds: Recovering Small Objects with Compact CNN Representations

3 code implementations CVPR 2017 Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, Teddy Furon, Ondrej Chum

The diffusion is carried out on descriptors of overlapping image regions rather than on a global image descriptor like in previous approaches.

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

Particular object retrieval with integral max-pooling of CNN activations

6 code implementations18 Nov 2015 Giorgos Tolias, Ronan Sicre, Hervé Jégou

Recently, image representation built upon Convolutional Neural Network (CNN) has been shown to provide effective descriptors for image search, outperforming pre-CNN features as short-vector representations.

Image Retrieval Re-Ranking

A comparison of dense region detectors for image search and fine-grained classification

no code implementations29 Oct 2014 Ahmet Iscen, Giorgos Tolias, Philippe-Henri Gosselin, Hervé Jégou

Our results show that the regular dense detector is outperformed by other methods in most situations, leading us to improve the state of the art in comparable setups on standard retrieval and fined-grain benchmarks.

General Classification Image Classification +1

Orientation covariant aggregation of local descriptors with embeddings

no code implementations8 Jul 2014 Giorgos Tolias, Teddy Furon, Hervé Jégou

Our geometric-aware aggregation strategy is effective for image search, as shown by experiments performed on standard benchmarks for image and particular object retrieval, namely Holidays and Oxford buildings.

Image Retrieval

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