Abstract
Pedestrian detection is one of the main research problems in the field of computer vision. With the development of deep learning technology, pedestrian detection algorithms have made great progress and breakthroughs. Currently, pedestrian detection technology using deep learning has become mainstream. The first type of algorithm is called two-stage detection algorithms, which are based on Region of Interest (ROI) and single-stage detection algorithms adopt an end-to-end training method. So this paper conducts extensive research on the basis of classification and comparison, studies the characteristics and development of the above two detection algorithms, respectively, and finally puts forward suggestions for their future development, such as the fusion of image background and target state.
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