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About the Synthetic Repetition #1973

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Cecilia-yu412 opened this issue Apr 1, 2024 · 3 comments
Open

About the Synthetic Repetition #1973

Cecilia-yu412 opened this issue Apr 1, 2024 · 3 comments

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@Cecilia-yu412
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Cecilia-yu412 commented Apr 1, 2024

Hi @debidatta,i'm trying to figure out how the period length labels are generated when training RepNet, . As it described in the paper,"Then, we sample a clip C of random length P frames from V. This clip C is repeated K times (where K > 1) to simulate videos with repetitions."Is there anything worth noting when choosing the length of clip C and doing the inversion and splicing to ensure good training results? For example, the way of generating random numbers and the choice of the number of repetitions, I hope your answer.

@Cecilia-yu412 Cecilia-yu412 changed the title period length labels About the Synthetic Repetition Apr 1, 2024
@Cecilia-yu412 Cecilia-yu412 reopened this Apr 1, 2024
@debidatta
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Yes you should ensure that the chosen segment gets repeated more than once. For example if you chose a segment of 32 frames or less it can repeat at least 2 times for the video length of 64. If you choose a longer segment it cannot repeat at least 2 times.

@Cecilia-yu412
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Yes you should ensure that the chosen segment gets repeated more than once. For example if you chose a segment of 32 frames or less it can repeat at least 2 times for the video length of 64. If you choose a longer segment it cannot repeat at least 2 times.

Thank you @debidatta, I got that. I have two other doubts, is it necessary to ensure that the number of duplicate clips of each synthetic video matches some distribution between 2~32 to prevent overfitting, or randint() has been sufficient? The second one is whether a large number of training sets are required for training? I want to synthesize the data on a training set of number about 800, roughly how many training samples should be generated, should i use a video for more than one time?

@debidatta
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is it necessary to ensure that the number of duplicate clips of each synthetic video matches some distribution between 2~32 to prevent overfitting, or randint() has been sufficient?

We used uniform sampling of period lengths. That is randint was sufficient.

The second one is whether a large number of training sets are required for training?

We were generating this data on the fly. For the final model we trained with batch size of 5 for 400k steps that is 2M synthetic repeating videos out of the 250k videos in Kinetics. That is about 8 synthetic videos per Kinetics video. You can possibly start with that or generate on the fly with more repeating videos per base video.

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