Currently, the overwhelming majority of NLVL models are top-down approaches: they first cut a video into a set of segment candidates, then they do classification and regression for each candidate.
they can be further grouped into two sub-types: 1) sliding-window-based (Gao et al., 2017;Hendricks et al., 2017;Liu et al., 2018b,a;Ge et al., 2019;Chen and Jiang, 2019;Xu et al., 2019;: the video is explicitly segmented by multiple predefined temporal sliding-window scales.