As a traditional form in NLP, the identification and comprehension of metaphor is a bottle-neck problem in NLP and machine translation. In this paper, based on the basic theory, current computational models for metaphor are reviewed. According to the methods, models are divided into metaphor identification and comprehension. The advantages of every model are also analyzed. At last, the paper introduces the current resources of metaphor processing.