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Temporal action localization is one of the most crucial and challenging problems for video understanding in computer vision. It has received a lot of attention in recent years because of the extensive application of daily life. Temporal action localization has made some significant progress, especially with the development of deep learning recently. And more demand is for temporal action localization in untrimmed videos. In this paper, our target is to survey the state-of-the-art techniques anddoi:10.1109/access.2020.2986861 fatcat:rsndgkzhi5fm5l6nmfmgfvugby