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AFOD: An Adaptable Framework for Object Detection in Event-based Vision
  • Shixiong Zhang ,
  • Wenmin Wang
Shixiong Zhang
International Institute of Next Generation Internet

Corresponding Author:[email protected]

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Wenmin Wang
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Event-based vision is a novel bio-inspired vision that has attracted the interest of many researchers. As a neuromorphic vision, the sensor is different from the traditional frame-based cameras. It has such advantages that conventional frame-based cameras can’t match, e.g., high temporal resolution, high dynamic range(HDR), sparse and minimal motion blur. Recently, a lot of computer vision approaches have been proposed with demonstrated success. However, there is a lack of some general methods to expand the scope of the application of event-based vision. To be able to effectively bridge the gap between conventional computer vision and event-based vision, in this paper, we propose an adaptable framework for object detection in event-based vision.