The application of computer vision (CV) in anesthesiology is gradually showing its potential and value, capable of enhancing the effectiveness of anesthesia, reducing the risk of complications, optimizing resource distribution, and improving work efficiency. This article reviews the current applications of CV in anesthesiology, including airway management, nerve blocks and punctures, monitoring the depth of anesthesia (DoA), and warning of perioperative-related complications. Meanwhile, it discusses the challenges faced in the current application, such as data acquisition, model training, interpretability, and robustness, and potential directions of future development, such as adopting new methods or technologies like mixed learning, transfer learning, and federated learning. CV is expected to profoundly affect the development of anesthesiology, promoting it to a higher level of precision medical care.