Comments (3)
Hi, could you please guide me on how to summarize my own video?
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Hi, could you please guide me on how to summarize my own video?
you have to extract features first for frames of the video and then based on trained model you can predict probability to be in a summary. For object features refer https://github.com/VideoAnalysis/EDUVSUM/tree/master/src
Motion feature code I will upload after refactoring.
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I fully agree with @pangzss. If my calculations are right, the used formula/command
y = torch.matmul(V.transpose(1,0), weights).transpose(1,0)
would be correct, only if the weights
array was symmetric, but this isn't the case.
Oddly enough, the produced results doesn't change much when the corrected formula/command is used.
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Related Issues (14)
- Extracted features for the datasets HOT 1
- Test my video
- problem about code,the coefficient of Spearman’s and Kendall’s in Tvsum are 0.5849 and 0.6403 HOT 5
- can't reproduce the f1 results, and coefficient results also seems unusual HOT 3
- Trained Model's F-score is different from the score stated in the paper. HOT 1
- how can I get the attribute 'gtscore' of SumMe?
- I use 'KTS' to segment the video ,but I can't get the result of yours,how can I get the same segmentation HOT 4
- extract object features HOT 6
- How did you extract the motion features for the datasets? HOT 2
- Which F1-Score is reported in the paper? HOT 1
- how to import i3d, i can not install by pip or conda HOT 1
- Request for changes in `train.py` and `knapsack.py`
- NOT able to reproduce spearman and kendall tau as reported in the paper.
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