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Initialization of LSTM layers #3
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Hi @limingqishi |
Hi @frajem I have finished the experiment. I got an accuracy of 94.24% on the UCF11 test set and 39.5% on the HMDB51 split1. How are your results? |
Hi @limingqishi Have you replicated the experiments of the paper ? I'm wondering, if you improved the acc. % of the paper. The reported UCF-11 accu % on paper are: Softmax Regression (full CNN feature cube) 82.37 I'm working on replicate the results, but I'm having lots of troubles. |
Hi @GerardoHH @kracwarlock |
@limingqishi @GerardoHH I had a query how can we test this code on UCF-11 dataset , when I downloaded the dataset from http://crcv.ucf.edu/data/UCF_YouTube_Action.php there are no .h5 files , so can you please help me in running this code , moreover what kind of computer specs are required to run this thing ( ram , os) ? Please do respond . |
Hi @rishabh135 |
@limingqishi can you please also help with what kind of computer will be sufficient to run this code , I have 4GB RAM with 2GB Nvidia Geforce 820M graphic card in windows 7 , will it suffice ? As I was reading other answers , I saw that it has been run with 48GB ram previously , so will I not be able to run this on my pc ? |
@rishabh135 |
@rishabh135 @limingqishi |
@GerardoHH @kracwarlock @limingqishi I am facing issue while running the script , I get "No GPU board available" error , any idea what is causing this , and also I am not entirely clear what features I have to extract (SIFT , HOG , SURF) from videos and then stack them to get the .h5 file , any help in this will be tremendously useful . |
Hi @limingqishi My running environment is, My config file of theano
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Hi everyone. I am sorry for all the delay. I was very busy with my thesis and graduation. I am no longer at the University of Toronto but will try to reply regularly here. |
@limingqishi The cell state and hidden state initialization happens in these lines: https://github.com/kracwarlock/action-recognition-visual-attention/blob/master/src/actrec.py#L368-L369
I see that I did not release the multi-layer LSTM code. I will try to do that as soon as I have time. Till then this is how it is done https://github.com/kelvinxu/arctic-captions/blob/master/capgen.py#L542-L548. In the paper the X means the feature of a single sample. In the code everything is done on a batch. |
@frajem @limingqishi @GerardoHH Yes UCF-11 has no standard train test split and the accuracy will depend on the split. That's why we didn't report any further results on it. You can overfit and perform very well. |
@rishabh135 Also take a look at my comments two posts above this one. I will try to make this easier as soon as possible. |
@rishabh135 https://github.com/kracwarlock/action-recognition-visual-attention/blob/5e3d0ab792195594cd422252cbac3f01333eb7ee/util/README.md#gpu-locking |
@limingqishi Did you use a 3-layer LSTM for the experiments on HMDB-51? If not, that would do the trick. If yes, let me know all your hyperparams. |
@kracwarlock how do we get the .h5 file from the youtube action dataset videos , do we need to first extract its features ("hog") and then stack them in a matrix , can anyone please mention a simple program to reduce the dataset to .h5 file and also what does train_labels.txt contain ? |
@rishabh135 If you can ask this on the relevant issue (#6) that would be great. If that issue does not cover your questions please open a separate issue. |
Hi @kracwarlock! I am also trying to reproduce your results on HMDB-51 and Hollywood2 (after reading this post I think I will skip the UCF-11). Can you please share the files valid_labels.txt, train_labels.txt, test_labels.txt, train_filenames.txt, test_filenames.txt and valid_filenames.txt for that two datasets? I will appreciate it a lot :) :) :) |
@jacopocavazza hey can you open a new issue for that since this is not related |
How did you initialize the cell state and the hidden state of the LSTM layers?
You gave an equation but didn't explain much. I wonder what the f_init function is. I read the code and guess it is a tanh function. How did you do that separately for the 3 layers? And I don't know what the X meant. Is it the feature of a single sample or a batch?
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