Fashion is a reflection of the society of a period. Given that New York City is one of the world's fashion capitals, understanding its change in fashion becomes a way to know the society and the times. To keep up with fashion trends, it is important to know what's "in" and what's "out" for a season. Though the fashion trends have been analyzed by fashion designers and fashion analysts for a long time, this issue has been ignored in multimedia science. In this paper, we present a novel algorithm that automatically discovers visual style elements representing fashion trends for a certain season. The visual style elements are discovered based on the stylistic coherent and unique characteristics. The experimental results demonstrate the effectiveness of our proposed method through a large number of catwalk show videos.