Research advanced in human pose estimation based on deep learning
YE XIA, Xinxue Jiang, Liaowenjin Yan · 2023
Human pose recognition is a current research hot spot, which aims to detect the information of human joints, orientations and scales from images or videos and predict the specific pose of the human body based on all the key point information. Benefiting from the rapid evolution of deep learning, target detection algorithms based on convolutional neural networks have achieved breakthroughs in both accuracy and efficiency. On the basis of detailed literature research and analysis, this paper provides a comprehensive evaluation of the research progress of human pose estimation. Specifically, we mainly introduce the classification of human action poses and the methods of human action pose recognition, including the design ideas, basic framework and advantages and disadvantages of representative recognition methods. Finally, we summarize the main challenges and give an outlook on the future research development of object detection.