Search Results for author: Joris Guérin

Found 9 papers, 3 papers with code

Combining Two Adversarial Attacks Against Person Re-Identification Systems

no code implementations24 Sep 2023 Eduardo de O. Andrade, Igor Garcia Ballhausen Sampaio, Joris Guérin, José Viterbo

We combine the use of two types of adversarial attacks, P-FGSM and Deep Mis-Ranking, applied to two popular Re-ID models: IDE (ResNet-50) and AlignedReID.

Image Classification Person Re-Identification

Out-Of-Distribution Detection Is Not All You Need

no code implementations29 Nov 2022 Joris Guérin, Kevin Delmas, Raul Sena Ferreira, Jérémie Guiochet

In this work, we argue that OOD detection is not a well-suited framework to design efficient runtime monitors and that it is more relevant to evaluate monitors based on their ability to discard incorrect predictions.

Out-of-Distribution Detection Out of Distribution (OOD) Detection

A novel method for object detection using deep learning and CAD models

no code implementations12 Feb 2021 Igor Garcia Ballhausen Sampaio, Luigy Machaca, José Viterbo, Joris Guérin

To do this, we created a Blender script that generates realistic labeled datasets of images containing the object, which are then used for training the OD model.

Object object-detection +1

Towards Practical Implementations of Person Re-Identification from Full Video Frames

no code implementations2 Sep 2020 Felix O. Sumari, Luigy Machaca, Jose Huaman, Esteban W. G. Clua, Joris Guérin

With the major adoption of automation for cities security, person re-identification (Re-ID) has been extensively studied recently.

Person Re-Identification

Semantically Meaningful View Selection

1 code implementation26 Jul 2018 Joris Guérin, Olivier Gibaru, Eric Nyiri, Stéphane Thiery, Byron Boots

Although deep learning has facilitated progress in image understanding, a robot's performance in problems like object recognition often depends on the angle from which the object is observed.

Clustering Object +1

Improving Image Clustering With Multiple Pretrained CNN Feature Extractors

1 code implementation20 Jul 2018 Joris Guérin, Byron Boots

For many image clustering problems, replacing raw image data with features extracted by a pretrained convolutional neural network (CNN), leads to better clustering performance.

Clustering Image Clustering

CNN features are also great at unsupervised classification

2 code implementations6 Jul 2017 Joris Guérin, Olivier Gibaru, Stéphane Thiery, Eric Nyiri

This paper aims at providing insight on the transferability of deep CNN features to unsupervised problems.

Classification Clustering +2

Clustering for Different Scales of Measurement - the Gap-Ratio Weighted K-means Algorithm

no code implementations22 Mar 2017 Joris Guérin, Olivier Gibaru, Stéphane Thiery, Eric Nyiri

This paper describes a method for clustering data that are spread out over large regions and which dimensions are on different scales of measurement.

Clustering

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