Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …

Spiking neural networks (SNNs) are inspired by information processing in biology, where
sparse and asynchronous binary signals are communicated and processed in a massively …

We present the first gesture recognition system implemented end-to-end on event-based
hardware, using a TrueNorth neurosynaptic processor to recognize hand gestures in real …

Event-based cameras have recently drawn the attention of the Computer Vision community
thanks to their advantages in terms of high temporal resolution, low power consumption and …

Neuromorphic vision research requires high-quality and appropriately challenging event-
stream datasets to support continuous improvement of algorithms and methods. However …

Creating datasets for Neuromorphic Vision is a challenging task. A lack of available
recordings from Neuromorphic Vision sensors means that data must typically be recorded …

Neuromorphic vision sensing (NVS) devices represent visual information as sequences of
asynchronous discrete events (aka," spikes'") in response to changes in scene reflectance …

Neuromorphic vision sensing (NVS) devices represent visual information as sequences of
asynchronous discrete events (aka,“spikes”) in response to changes in scene reflectance …

2. Materials and Methods The DVS data are generated by displaying existing benchmark
videos on a monitor, and recording with a stationary DAViS240C vision sensor under …

Large-scale public datasets are vital for algorithm development in the computer vision field.
Thanks to the availability of advanced sensors such as cameras, Lidar and Kinect, massive …