ubuntu 安装openblas,从而安装Theano
2016-09-23 00:18
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这个是我遇到的问题~
https://github.com/xianyi/OpenBLAS/issues/179
We use multi-layered Recurrent Neural Networks (RNNs) with Long-Short Term Memory
(LSTM) units which are deep both spatially and temporally. Our model learns to focus
selectively on parts of the video frames and classifies videos after taking a few
glimpses. The model essentially learns which parts in the frames are relevant for the
task at hand and attaches higher importance to them. We evaluate the model on UCF-11
(YouTube Action), HMDB-51 and Hollywood2 datasets and analyze how the model focuses its
attention depending on the scene and the action being performed.
NumPy
scikit learn
skimage
Theano
h5py
following papers:
“Action Recognition using Visual Attention.”
Shikhar Sharma, Ryan Kiros, Ruslan Salakhutdinov. arXiv
“Show, Attend and Tell: Neural Image Caption Generation with Visual Attention.”
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan
Salakhutdinov, Richard Zemel, Yoshua Bengio. To appear ICML (2015)
is the implementation for our paper Action Recognition using Visual Attention. The repository uses some code from the project
arctic-caption which is originally the implementation for the paper
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention and is also licensed
under a revised (3-clause) BSD License
https://github.com/xianyi/OpenBLAS/issues/179
Action Recognition using Visual Attention
We propose a soft attention based model for the task of action recognition in videos.We use multi-layered Recurrent Neural Networks (RNNs) with Long-Short Term Memory
(LSTM) units which are deep both spatially and temporally. Our model learns to focus
selectively on parts of the video frames and classifies videos after taking a few
glimpses. The model essentially learns which parts in the frames are relevant for the
task at hand and attaches higher importance to them. We evaluate the model on UCF-11
(YouTube Action), HMDB-51 and Hollywood2 datasets and analyze how the model focuses its
attention depending on the scene and the action being performed.
Dependencies
Python 2.7NumPy
scikit learn
skimage
Theano
h5py
Reference
If you use this code as part of any published research, please acknowledge thefollowing papers:
“Action Recognition using Visual Attention.”
Shikhar Sharma, Ryan Kiros, Ruslan Salakhutdinov. arXiv
@article{sharma2015attention, title={Action Recognition using Visual Attention}, author={Sharma, Shikhar and Kiros, Ryan and Salakhutdinov, Ruslan}, journal={arXiv preprint arXiv:1511.04119}, year={2015} }
“Show, Attend and Tell: Neural Image Caption Generation with Visual Attention.”
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan
Salakhutdinov, Richard Zemel, Yoshua Bengio. To appear ICML (2015)
@article{Xu2015show, title={Show, Attend and Tell: Neural Image Caption Generation with Visual Attention}, author={Xu, Kelvin and Ba, Jimmy and Kiros, Ryan and Cho, Kyunghyun and Courville, Aaron and Salakhutdinov, Ruslan and Zemel, Richard and Bengio, Yoshua}, journal={arXiv preprint arXiv:1502.03044}, year={2015} }
License
This repsoitory is released under a revised (3-clause) BSD License. Itis the implementation for our paper Action Recognition using Visual Attention. The repository uses some code from the project
arctic-caption which is originally the implementation for the paper
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention and is also licensed
under a revised (3-clause) BSD License
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