SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.

[IEEE TCYB 2023] The first large-scale tracking dataset by fusing RGB and Event cameras.

Resources Related to Event-based Vision | Event Cameras | DVS

EVDodgeNet: Deep Dynamic Obstacle Dodging with event cameras

interfaces and algorithms for event based cameras, lidars, and actuators

The Only Calculator App You'll Ever Need.

A unified framework for event-based video. Encoder/transcoder/decoder for ADΔER (Address, Decimation, Δt Event Representation) video streams.

Offical implementation of "Adaptive Smoothing Gradient Learning for Spiking Neural Networks", ICML 2023

Inceptive Event Time Surfaces (ICIAR 2019)

Post-synthesis power optimization via dual-Vth cell assignment and gate re-sizing. Scripting in TCL with custom commands written for Synopsys® PrimeTime® and DC Ultra™.

Real-time task simulator supporting DVS-HM, DVS-DRAM, HM

STBP (Spatio Temporal Back Propagation) implemented on SL-Animals-DVS dataset for training Spiking Neural Networks

Python tools to process and visualize address-event data from dynamic vision sensors such as DVS128

Machine Learning tools for Dynamic Vision Sensors such as DVS128

Rust port of https://github.com/MartinNowak96/AEDAT-File-Reader

Reconstructing a depth map by from two DAVIS and a controlled laser.

SLAYER (Spiking Layer Error Reassignment in Time) implemented on SL-Animals-DVS dataset for training Spiking Neural Networks

DECOLLE (Deep Continuous Local Learning) implemented on SL-Animals-DVS dataset for training Spiking Neural Networks

Openstack VSphere DVS driver with Hierarchical Portbinding and Security Groups using Traffic-& Marking of the DVS