Patent ID: 11941872
Assignee: ZHEJIANG GONGSHANG UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 5:
6. The method according to claim 5, wherein step 5 comprises:
step 5-1: sampling the video feature obtained in step 1 with a second step size to obtain a series of temporally ordered basic clip feature vectors;
step 5-2: updating the basic clip feature vectors by a conditional feature update module by using the intermediate feature map obtained in step 4-1, and obtaining a series of temporally continuous clips through a combination of the basic clips; wherein a current stage is desired to be focused on an area that have great relevance to the text, which has been learned in the coarse time granularity localization stage; the conditional feature update module is to update the features of the current stage by learning weights by using information in the coarse time granularity localization stage; and
step 5-3: selecting candidate clips from all possible clips by sparse sampling strategy, performing the maximum pooling operation on the basic clips in each candidate clip interval to obtain the features of the candidate clip, and representing the features of all candidate clips with the two-dimensional feature map to obtain the two-dimensional feature map of the candidate clips during fine time granularity localization.