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It seems that the 1st-5th group won't be changing weights during the training since there is a pre-trained model in your description below:
"The C3D model weight pretrained on Sports1M and finetuned on ActivityNet dataset"
Is this a correct understanding?
Can you provide a more comprehensive expalantion about "end-to-end", in terms of training via back-propagation? For instance, maybe we can use your paper's Fighure 2 as a reference.
Thanks a lot!
The text was updated successfully, but these errors were encountered:
The learning rate at these layers can also be open. But the training time will increase. It is a trade-off.
On Jan 29, 2019, at 09:49, rambleramble <[email protected]<mailto:[email protected]>> wrote:
It seems that the 1st-5th group won't be changing weights during the training since there is a pre-trained model in your description<https://github.com/VisionLearningGroup/R-C3D/blob/master/experiments/thumos14/train.prototxt>
"The C3D model weight pretrained on Sports1M and finetuned on ActivityNet dataset"
Is this a correct understanding?
Can you provide a more comprehensive expalantion about "end-to-end", in terms of training via back-propagation? For instance, maybe we can use your paper's Fighure 2 as a reference.
Thanks a lot!
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It seems that the 1st-5th group won't be changing weights during the training since there is a pre-trained model in your description below:
"The C3D model weight pretrained on Sports1M and finetuned on ActivityNet dataset"
Is this a correct understanding?
Can you provide a more comprehensive expalantion about "end-to-end", in terms of training via back-propagation? For instance, maybe we can use your paper's Fighure 2 as a reference.
Thanks a lot!
The text was updated successfully, but these errors were encountered: