298 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université de LilleFR364 papers
- Centre National de la Recherche ScientifiqueFR257 papers
- École Centrale de LilleFR212 papers
- Centre de Recherche en InformatiqueFR203 papers
- Université Paris-SaclayFR74 papers
- Institut d'Astrophysique SpatialeFR64 papers
- Sorbonne UniversitéFR59 papers
- Institut de Recherche en Astrophysique et PlanétologieFR58 papers
- Université Paris CitéFR57 papers
- Université Paris Sciences et LettresFR53 papers
- Ludwig-Maximilians-Universität MünchenDE52 papers
- CEA Paris-SaclayFR51 papers
32 papers · 1 filter
Privacy-Preserving Person Re-Identification from Temporal Sequences with Transformer and Hungarian Optimization
Raphaël Delécluse, Hazem Wannous, Laurent Guimas
Person re-identification (Re-ID) is a crucial task in surveillance and human behavior analysis, often used in public spaces such as transport hubs. Traditional RGB-based Re-ID meth…
DinoLizer: Separating VAE and Diffusion Artifacts in Generative Inpainting Localization
Minh Thong Doi, Vincent Itier, Jan Butora +2
We introduce DinoLizer, a DINOv2-based localizer of manipulated areas in generative inpainting. The model is trained to focus on semantically altered regions by treating reconstruc…
Online hand gesture recognition using Continual Graph Transformers
Rim Slama, Wael Rabah, Hazem Wannous
Online continuous action recognition has emerged as a critical research area due to its practical implications in real-world applications, such as human-computer interaction, healt…
A survey on Graph Deep Representation Learning for Facial Expression Recognition
Théo Gueuret, Akrem Sellami, Chaabane Djeraba
This comprehensive review delves deeply into the various methodologies applied to facial expression recognition (FER) through the lens of graph representation learning (GRL). Initi…
Neuronal Competition Groups with Supervised STDP for Spike-Based Classification
Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco
Spike Timing-Dependent Plasticity (STDP) is a promising substitute to backpropagation for local training of Spiking Neural Networks (SNNs) on neuromorphic hardware. STDP allows SNN…
Beyond Fixed Topologies: Unregistered Training and Comprehensive Evaluation Metrics for 3D Talking Heads
Federico Nocentini, Thomas Besnier, Claudio Ferrari +3
Generating speech-driven 3D talking heads presents numerous challenges; among those is dealing with varying mesh topologies where no point-wise correspondence exists across the mes…
Basis restricted elastic shape analysis on the space of unregistered surfaces
Emmanuel Hartman, Emery Pierson, Martin Bauer +2
This paper introduces a new mathematical and numerical framework for surface analysis derived from the general setting of elastic Riemannian metrics on shape spaces. Traditionally,…
S3TC: Spiking Separated Spatial and Temporal Convolutions with Unsupervised STDP-based Learning for Action Recognition
Mireille El-Assal, Pierre Tirilly, Ioan Marius Bilasco
Video analysis is a major computer vision task that has received a lot of attention in recent years. The current state-of-the-art performance for video analysis is achieved with De…
Paired Competing Neurons Improving STDP Supervised Local Learning In Spiking Neural Networks
Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco
Direct training of Spiking Neural Networks (SNNs) on neuromorphic hardware has the potential to significantly reduce the energy consumption of artificial neural network training. S…
Generating Multiple 4D Expression Transitions by Learning Face Landmark Trajectories
Naima Otberdout, Claudio Ferrari, Mohamed Daoudi +2
In this work, we address the problem of 4D facial expressions generation. This is usually addressed by animating a neutral 3D face to reach an expression peak, and then get back to…
Interaction Transformer for Human Reaction Generation
Baptiste Chopin, Hao Tang, Naima Otberdout +2
We address the challenging task of human reaction generation, which aims to generate a corresponding reaction based on an input action. Most of the existing works do not focus on g…
2D versus 3D Convolutional Spiking Neural Networks Trained with Unsupervised STDP for Human Action Recognition
Mireille El-Assal, Pierre Tirilly, Ioan Marius Bilasco
Current advances in technology have highlighted the importance of video analysis in the domain of computer vision. However, video analysis has considerably high computational costs…
Self-mentoring: a new deep learning pipeline to train a self-supervised U-net for few-shot learning of bio-artificial capsule segmentation
Arnaud Deleruyelle, Cristian Versari, John Klein
Background: Accurate segmentation of microscopic structures such as bio-artificial capsules in microscopy imaging is a prerequisite to the computer-aided understanding of important…
3D Skeleton-based Human Motion Prediction with Manifold-Aware GAN
Baptiste Chopin, Naima Otberdout, Mohamed Daoudi +1
In this work we propose a novel solution for 3D skeleton-based human motion prediction. The objective of this task consists in forecasting future human poses based on a prior skele…
Mining atmospheric data
Chaabane Djeraba, Jérôme Riedi
This paper overviews two interdependent issues important for mining remote sensing data (e.g. images) obtained from atmospheric monitoring missions. The first issue relates the bui…
A Study On the Effects of Pre-processing On Spatio-temporal Action Recognition Using Spiking Neural Networks Trained with STDP
El-Assal Mireille, Tirilly Pierre, Bilasco Ioan Marius
There has been an increasing interest in spiking neural networks in recent years. SNNs are seen as hypothetical solutions for the bottlenecks of ANNs in pattern recognition, such a…
Deep Spiking Convolutional Neural Network for Single Object Localization Based On Deep Continuous Local Learning
Sami Barchid, José Mennesson, Chaabane Djéraba
With the advent of neuromorphic hardware, spiking neural networks can be a good energy-efficient alternative to artificial neural networks. However, the use of spiking neural netwo…
Human Motion Prediction Using Manifold-Aware Wasserstein GAN
Baptiste Chopin, Naima Otberdout, Mohamed Daoudi +1
Human motion prediction aims to forecast future human poses given a prior pose sequence. The discontinuity of the predicted motion and the performance deterioration in long-term ho…
Dynamic Facial Expression Recognition under Partial Occlusion with Optical Flow Reconstruction
Delphine Poux, Benjamin Allaert, Nacim Ihaddadene +3
Video facial expression recognition is useful for many applications and received much interest lately. Although some solutions give really good results in a controlled environment…
Improving STDP-based Visual Feature Learning with Whitening
Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco
In recent years, spiking neural networks (SNNs) emerge as an alternative to deep neural networks (DNNs). SNNs present a higher computational efficiency using low-power neuromorphic…
Sparse Coding of Shape Trajectories for Facial Expression and Action Recognition
Amor Ben Tanfous, Hassen Drira, Boulbaba Ben Amor
The detection and tracking of human landmarks in video streams has gained in reliability partly due to the availability of affordable RGB-D sensors. The analysis of such time-varyi…
Dynamic Facial Expression Generation on Hilbert Hypersphere with Conditional Wasserstein Generative Adversarial Nets
Naima Otberdout, Mohamed Daoudi, Anis Kacem +2
In this work, we propose a novel approach for generating videos of the six basic facial expressions given a neutral face image. We propose to exploit the face geometry by modeling…
Impact of facial landmark localization on facial expression recognition
Romain Belmonte, Benjamin Allaert, Pierre Tirilly +3
Although facial landmark localization (FLL) approaches are becoming increasingly accurate for characterizing facial regions, one question remains unanswered: what is the impact of…
Facial Expressions Analysis Under Occlusions Based on Specificities of Facial Motion Propagation
Delphine Poux, Benjamin Allaert, Jose Mennesson +3
Although much progress has been made in the facial expression analysis field, facial occlusions are still challenging. The main innovation brought by this contribution consists in…