Comments (3)
HMDB-51 provides three train-test splits . We just used split 1. Hollywood2 also provides a train-test split. For validation we used 15% of the training data as validation set and the rest 85% for training. We noted the cost at best performance on the validation set. We then trained on the entire training data until the cost reached the same value as noted with the validation set separated.
Will share the txt files.
from action-recognition-visual-attention.
@kracwarlock Hi, also hope you can share your txt files, Thanks
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I am trying to figure out how was the 1st attention initialized. In the attached figure, l1?
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Related Issues (20)
- some question about the input and output of the LSTM HOT 2
- ucf11 evaluation problem HOT 1
- Location softmax HOT 4
- Multi-layer LSTM
- How to get the dataset? HOT 2
- Your time for one 128-batch? HOT 5
- How to get the h5 features file,how to create h5 features file
- Possible bug on data_handler : Reset()
- Python Scripts for CNN Encoding Generation HOT 1
- Input data HOT 10
- Can anyone share the code mentioned in the closed issue #6 which is used to combine features to h5 format? HOT 3
- I'm new to this task. Could I know that how many frame are feed in testing time?
- Initialization of LSTM layers HOT 21
- Best model selection HOT 1
- 1
- Can you elaborate how to do data preprocessing? HOT 23
- How the soft attention model be implemented in this project? HOT 1
- Enquiries regarding Data Preprocessing HOT 1
- Possible redundant code in actrec_mAP.py HOT 1
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