Comments (28)
This function generates a summary from summary of 20 users in the dataset.
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The implementation is based on which paragraph of FSCN paper or other paper?
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Chapter 3.1 of this paper: Diverse sequential subset selection for supervised video summarization. In my implementation, the greedy algorithm selects the frame marked by the most users each time.
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After reading Chapter 3.1, I still cannot realize the process.
Given 3 human summaries with 5 frames:
A: [1,0,1,1,0]
B: [0,0,1,0,0]
C: [0,0,0,1,0]
How to get the final summary?
First: calculate the select times of each frame -> [1,0,2,2,0]
Second: I have no idea...
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In my implementation, initialize oracle summary as [0, 0, 0, 0, 0], and then pick the most selected frame (here the third), now the oracle summary will be [0, 0, 1, 0, 0]. Determine if the F-score between oracle summary and user summary increases after adding this frame. If true, continue to select next frame, otherwise it ends.
But it is just my implementation, I didn't find a specific description of the greedy algorithm used in the paper. So I'm not sure if the algorithm is like this.
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Where is FCSN mentioned that they use "Diverse sequential subset selection for supervised video summarization" for generating a summary from summary of users?
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This method is mentioned in supplementary materials of paper Video Summarization with Long Short-term Memory.
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After I read the paragraph, I implement it.
Is my understanding identical to yours?
But the performance is quite bad...
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Have you print the final F-score between generated oracle summary and user summary?
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Did you mean the parameter "best_fscore"?
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It seems slightly different.
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I found that tvsum use avg but summe use max when evaluating.
After I change summe to max, my result gets better.
But I do not know why to use this method...
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Could you share the tvsum video on your google drive?
tvsum needs authorization....
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I found that tvsum use avg but summe use max when evaluating.
After I change summe to max, my result gets better.But I do not know why to use this method...
Is this result on SumMe? It seems close to that in paper!
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Could you share the tvsum video on your google drive?
tvsum needs authorization....
Wait a moment, I'm now uploading it...
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https://github.com/KaiyangZhou/pytorch-vsumm-reinforce/blob/fdd03be93f090278424af789c120531e49aefa40/main.py#L164
I found that tvsum use avg but summe use max when evaluating.
After I change summe to max, my result gets better.
But I do not know why to use this method...
Is this result on SumMe? It seems close to that in paper!
Yes, it is summe.
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Could you share the tvsum video on your google drive?
tvsum needs authorization....Wait a moment, I'm now uploading it...
Thank you
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Here is the link.
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Got it. Thank you very much.
Did you figure out ?
https://github.com/KaiyangZhou/pytorch-vsumm-reinforce/blob/fdd03be93f090278424af789c120531e49aefa40/main.py#L164
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May be it is a default setting in evaluation? I also think it's strange...
And I noticed that selected key frames of videos in summe differ greatly from each user, F-score between generated oracle summary and user summary is only nearly 50%, but that is nearly 70% in tvsum. In this case, getting a summary close to every user seems to be difficult. Is this probably a reason to select max?
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I agree with your opinion. Let's take this evaluation method for granted.
I also implement this paper which architecture is based on FCSN but there are some problems...
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I have not read this paper yet, its architecture looks complicated.
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Do you have any idea of FCSN in unsupervised version?
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No... I skip that part when reading the paper...
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Shall we implement that part?
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I will try to implement it after reading that part, but there may be some problems because my computer at home doesn't have a nvidia gpu 😅😅
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I am counting on you.
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Here is the link.
Thanks for this.
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Related Issues (20)
- Hello,Can you send me a dataset? HOT 4
- Hello,can you tell me the concrete structure of the unsupervised FCSN?
- gen_summary failed with IndexError HOT 6
- Is it able to summarize a custom video? HOT 1
- The architecture of the FCSN is different from the paper
- Could you share the SumMe dataset on your google drive?
- KeyError: "Unable to open object (object 'video_tensor(41)' doesn't exist)" HOT 10
- Can you provide‘.h5’ files under three settings of dataset?
- provide data/files (ydata-tvsum50-v1_1)
- hello,Are you the author of the paper?
- How to do this in colab
- index 5866 is out of bounds for axis 0 with size 5846 HOT 1
- A mistake in train.py line 48
- Implementation of Reconstruction and Diversity loss
- Is the model same as discussed in the paper??
- IndexError: index 202 is out of bounds for axis 0 with size 0 HOT 1
- fcsn_dataset.h5
- train on my own dataset
- How test this on single video?
- unable 同openobject(object ‘video_-esJrBWj2d8’ doesn't exit)
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