A deep-learning-based stereo matching method for a binocular dynamic vision sensor, the method comprising the following steps: 1) generating training point pairs according to depth information in a data set of a binocular event camera; 2) constructing a representation mode suitable for events in an event flow of a dynamic vision sensor; and 3) representing the event training point pairs according to the representation mode, and transmitting same to twin neural networks for training, and performing stereo matching according to a training result. Compared with the prior art, the method has the advantages of high matching precision and a fast matching speed.
DEEP-LEARNING-BASED STEREO MATCHING METHOD FOR BINOCULAR DYNAMIC VISION SENSOR