GuangmingZhu / AttentionConvLSTM

"Attention in Convolutional LSTM for Gesture Recognition" in NIPS 2018
http://papers.nips.cc/paper/7465-attention-in-convolutional-lstm-for-gesture-recognition
MIT License
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AttentionConvLSTM

Prerequisites

1) Python 2.7 2) Tensorflow-1.2
3) The implementation files of the variants of ConvLSTM are in the local dir "patchs". You need merge them with the corresponding files of TF-1.2.

Get the pretrained models

The trained models can be obtained from the below link:
Link: https://pan.baidu.com/s/1O-U_Q-5i9wxOA0MDyi3Idg Code: immi

How to use the code

Prepare the data

1) Convert each video files into images. 2) Replace the path "/ssd/dataset" in the files under "dataset_splits"

Training

1) Use training_*.py to train the networks for different datasets and different modalities.

Testing

1) Use testing_*.py to evaluate the trained networks on the valid or test subsets of Jester or IsoGD.

Citation

Please cite the following paper if you feel this repository useful.
http://papers.nips.cc/paper/7465-attention-in-convolutional-lstm-for-gesture-recognition http://openaccess.thecvf.com/content_ICCV_2017_workshops/w44/html/Zhang_Learning_Spatiotemporal_Features_ICCV_2017_paper.html http://ieeexplore.ieee.org/abstract/document/7880648/

@article{ZhuNIPS2018,
  title={Attention in Convolutional LSTM for Gesture Recognition},
  author={Liang Zhang and Guangming Zhu and Lin Mei and Peiyi Shen and Syed Afaq Shah and Mohammed Bennamoun},
  journal={NIPS},
  year={2018}
}
@article{ZhuICCV2017,
  title={Learning Spatiotemporal Features using 3DCNN and Convolutional LSTM for Gesture Recognition},
  author={Liang Zhang and Guangming Zhu and Peiyi Shen and Juan Song and Syed Afaq Shah and Mohammed Bennamoun},
  journal={ICCV},
  year={2017}
}
@article{Zhu2017MultimodalGR,
  title={Multimodal Gesture Recognition Using 3-D Convolution and Convolutional LSTM},
  author={Guangming Zhu and Liang Zhang and Peiyi Shen and Juan Song},
  journal={IEEE Access},
  year={2017},
  volume={5},
  pages={4517-4524}
}

Contact

For any question, please contact

  gmzhu@xidian.edu.cn