A Survey on Video Moment Localization
Meng Liu Liqiang Nie Yunxiao Wang Meng Wang Yong Rui
Video moment localization, also known as video moment retrieval, aiming to
search a target segment within a video described by a given natural language
query. Beyond the task of temporal action localization whereby the target
actions are pre-defined, video moment retrieval can query arbitrary complex
activities. In this survey paper, we aim to present a comprehensive review of
existing video moment localization techniques, including supervised, weakly
supervised, and unsupervised ones. We also review the datasets available for
video moment localization and group results of related work. In addition, we
discuss promising future directions for this field, in particular large-scale
datasets and interpretable video moment localization models.