Human-Level Performance is the error a person may get. It's usually based on what your objective is. On the opposite to that is the Bayes (optimal) error which is the theoretical error. And this error may not be 0. Since there might be some impossible cases to classify, e.g., a picture that is too blurry to be recognized. Before surpassing human-level performance, the accuracy will be improved greatly. However, when it passes the line, it will get harder since you cannot learn from human, and you don't know what the true Bayes error is.