Event-based vision
43 papers with code • 1 benchmarks • 9 datasets
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.
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Latest papers
SEVD: Synthetic Event-based Vision Dataset for Ego and Fixed Traffic Perception
In response to this gap, we present SEVD, a first-of-its-kind multi-view ego, and fixed perception synthetic event-based dataset using multiple dynamic vision sensors within the CARLA simulator.
Detecting Every Object from Events
Object detection is critical in autonomous driving, and it is more practical yet challenging to localize objects of unknown categories: an endeavour known as Class-Agnostic Object Detection (CAOD).
State Space Models for Event Cameras
We address this challenge by introducing state-space models (SSMs) with learnable timescale parameters to event-based vision.
LEOD: Label-Efficient Object Detection for Event Cameras
On 1Mpx, RVT-S with 10% labels even surpasses its fully-supervised counterpart using 100% labels.
Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Networks
Spiking Neural Networks (SNNs) have emerged as a promising energy-efficient alternative to traditional Artificial Neural Networks (ANNs).
Event-based Background-Oriented Schlieren
Schlieren imaging is an optical technique to observe the flow of transparent media, such as air or water, without any particle seeding.
GET: Group Event Transformer for Event-Based Vision
Event cameras are a type of novel neuromorphic sen-sor that has been gaining increasing attention.
CrossZoom: Simultaneously Motion Deblurring and Event Super-Resolving
Even though the collaboration between traditional and neuromorphic event cameras brings prosperity to frame-event based vision applications, the performance is still confined by the resolution gap crossing two modalities in both spatial and temporal domains.
Person Re-Identification without Identification via Event Anonymization
In this work, we also bring to the community the first ever event-based person ReId dataset gathered to evaluate the performance of our approach.
On the Generation of a Synthetic Event-Based Vision Dataset for Navigation and Landing
We anticipate that novel event-based vision datasets can be generated using this pipeline to support various spacecraft pose reconstruction problems given events as input, and we hope that the proposed methodology would attract the attention of researchers working at the intersection of neuromorphic vision and guidance navigation and control.