关键词: 深度学习, 目标检测, 卷积神经网络, 计算机视觉

Abstract: After the R-CNN framework is proposed, the object detection framework based on deep learning has gradually become the mainstream, which can be divided into one-stage and two-stage. In the past two years, based on the classic deep learning object detection frameworks such as Faster R-CNN, YOLO, and SSD, a large number of excellent frameworks have emerged. Firstly, according to the optimization method, the frameworks proposed in the past few years are sorted out and summarized. Then, the performance of the object detection methods is compared on the mainstream test sets such as PASCAL_VOC and MS COCO. The advantages and disadvantages are analyzed. Finally, the current difficulties and challenges in the field are discussed, and the possible development directions are prospected.

Key words: deep learning, object detection, convolutional neural networks, computer vision