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What is Pseudo-Labeling for DVS Object Detection about?

This paper presents a method for generating pseudo-labels for dynamic vision sensor (DVS) data to facilitate supervised learning in object detection, particularly under ego-motion. By leveraging corresponding frame-based data, the authors demonstrate that a convolutional neural network (CNN) can effectively detect cars from DVS data at high speeds, achieving an average precision of 41.7%. The proposed approach addresses the challenge of limited labeled data in event-based computer vision, paving the way for

Author

nqwce2b2k

Language

EN