activity
20192025
most citedUnsupervised Visual Feature Learning with Spike-timing-dependent Plasticity: How Far are we from Traditional Feature Learning Approaches?

46 citations · 74 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2025

Frozen Backpropagation: Relaxing Weight Symmetry in Deep Spiking Neural Networks

Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco

Direct training of Spiking Neural Networks (SNNs) on neuromorphic hardware can greatly reduce energy costs compared to GPU-based training. However, implementing Backpropagation (BP…

cs.CV2024★ 1 cited

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…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 10 cited

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…

cs.CV2023★ 2 cited

Spiking Two-Stream Methods with Unsupervised STDP-based Learning for Action Recognition

Mireille El-Assal, Pierre Tirilly, Ioan Marius Bilasco

Video analysis is a computer vision task that is useful for many applications like surveillance, human-machine interaction, and autonomous vehicles. Deep Convolutional Neural Netwo…

cs.CV2022

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…

cs.CV2021★ 7 cited

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…

cs.CV2020★ 6 cited

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…

cs.CV2019★ 1 cited

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…

cs.CV2019

Multi-layered Spiking Neural Network with Target Timestamp Threshold Adaptation and STDP

Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco +2

Spiking neural networks (SNNs) are good candidates to produce ultra-energy-efficient hardware. However, the performance of these models is currently behind traditional methods. Int…

cs.CV2019★ 46 cited

Unsupervised Visual Feature Learning with Spike-timing-dependent Plasticity: How Far are we from Traditional Feature Learning Approaches?

Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco +2

Spiking neural networks (SNNs) equipped with latency coding and spike-timing dependent plasticity rules offer an alternative to solve the data and energy bottlenecks of standard co…