SOTAVerified

Event-based vision

An event camera, also known as a neuromorphic camera, silicon retina or dynamic vision sensor, is an imaging sensor that responds to local changes in brightness. Event cameras do not capture images using a shutter as conventional cameras do. Instead, each pixel inside an event camera operates independently and asynchronously, reporting changes in brightness as they occur and staying silent otherwise. Modern event cameras have microsecond temporal resolution, 120 dB dynamic range, and less under/overexposure and motion blur than frame cameras.

Papers

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Showing 121–130 of 145 papers

TitleStatusHype
Secrets of Edge-Informed Contrast Maximization for Event-Based Vision—0
An error-propagation spiking neural network compatible with neuromorphic processors—0
Unsupervised Domain Adaptation for Training Event-Based Networks Using Contrastive Learning and Uncorrelated Conditioning—0
A Framework for Pupil Tracking with Event Cameras—0
3D Human Scan With A Moving Event Camera—0
Spatiotemporal Feature Learning for Event-Based Vision—0
Speck: A Smart event-based Vision Sensor with a low latency 327K Neuron Convolutional Neuronal Network Processing Pipeline—0
SpiDR: A Reconfigurable Digital Compute-in-Memory Spiking Neural Network Accelerator for Event-based Perception—0
Spike-time encoding of gas concentrations using neuromorphic analog sensory front-end—0
AET-EFN: A Versatile Design for Static and Dynamic Event-Based Vision—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1REDmAP43—Unverified