Search Results for author: Céline Teulière

Found 9 papers, 4 papers with code

Seeing the Whole in the Parts in Self-Supervised Representation Learning

no code implementations6 Jan 2025 Arthur Aubret, Céline Teulière, Jochen Triesch

Here, we propose a new way to model spatial co-occurrences by aligning local representations (before pooling) with a global image representation.

Representation Learning Self-Supervised Learning

Predictive Coding with Spiking Neural Networks: a Survey

no code implementations9 Sep 2024 Antony W. N'dri, William Gebhardt, Céline Teulière, Fleur Zeldenrust, Rajesh P. N. Rao, Jochen Triesch, Alexander Ororbia

In this article, we review a class of neuro-mimetic computational models that we place under the label of spiking predictive coding.

Edge-computing Prediction +1

Self-supervised visual learning from interactions with objects

1 code implementation9 Jul 2024 Arthur Aubret, Céline Teulière, Jochen Triesch

In our analysis, we find that the observed improvement is associated with a better viewpoint-wise alignment of different objects from the same category.

Object Representation Learning +1

Time to augment self-supervised visual representation learning

no code implementations27 Jul 2022 Arthur Aubret, Markus Ernst, Céline Teulière, Jochen Triesch

Specifically, our analyses reveal that: 1) 3-D object manipulations drastically improve the learning of object categories; 2) viewing objects against changing backgrounds is important for learning to discard background-related information from the latent representation.

Contrastive Learning Object +2

Embodied vision for learning object representations

no code implementations12 May 2022 Arthur Aubret, Céline Teulière, Jochen Triesch

During each play session the agent views an object in multiple orientations before turning its body to view another object.

Contrastive Learning Object +1

Leveraging blur information for plenoptic camera calibration

3 code implementations9 Nov 2021 Mathieu Labussière, Céline Teulière, Frédéric Bernardin, Omar Ait-Aider

This paper presents a novel calibration algorithm for plenoptic cameras, especially the multi-focus configuration, where several types of micro-lenses are used, using raw images only.

Camera Calibration

Blur Aware Calibration of Multi-Focus Plenoptic Camera

1 code implementation16 Apr 2020 Mathieu Labussière, Céline Teulière, Frédéric Bernardin, Omar Ait-Aider

This paper presents a novel calibration algorithm for Multi-Focus Plenoptic Cameras (MFPCs) using raw images only.

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