With the rapid developments in science and technology and the continuous iteration of hardware equipment, artificial intelligence is being widely used in various fields (such as security monitoring, medical assistance, health diagnosis, intelligent recommendation, remote sensing monitoring, and target location). With the gradual expansion of user requirements for intelligent processing tasks, semantic understanding levels and accuracy requirements of intelligent algorithms are also gradually increasing. As such, the pixel-level task of semantic understanding, which requires much higher accuracy than image-level understanding, is attracting increasing attention. Compared to image-level understanding, in addition to the large amount and high precision of pixel-by-pixel output, the internal challenges in pixel-level semantic understanding merit greater attention and research. From the information measurement perspective, and given the unique attributes of pixel-level semantic understanding, in this paper, we present the definition and optimization goal of pixel-level semantic understanding, and derive pixel-level semantic classification and pixel-level semantic regression from the original definition based on the characteristics of actual tasks. We then discuss the degradation and evolution of optimization objectives in these two subcategories, respectively. Based on a detailed investigation, we summarize the development and current status of typical tasks in pixel-level semantic understanding. We consider the difficulties and future development direction of the current pixel-level semantic understanding, perform an in-depth analysis, and suggest feasible solutions to problems that require urgent solutions. Finally, we focus on the opportunities and challenges faced by pixel-level semantic understanding, and even artificial intelligence, in the post-deep-learning era and argue that knowledge guidance and data-driven optimization are fundamental objectives for the future development of artificial intelligence. From the definition and current development of pixel-level semantic understanding, in this work, we extend the current conceptual approach and reflect on the risks faced by the whole field, providing an in-depth discussion and consideration of the developmental direction of related technologies, while clarifying the knowledge base of pixel-level semantic understanding.