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LSTA: Long Short-Term Attention for Egocentric Action Recognition

We release the PyTorch code of LSTA

LSTA

Reference

Please cite our paper if you find the repo and the paper useful.

@InProceedings{Sudhakaran_2019_CVPR,
author = {Sudhakaran, Swathikiran and Escalera, Sergio and Lanz, Oswald},
title = {{LSTA: Long Short-Term Attention for Egocentric Action Recognition}},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}

Prerequisites

  • Python 3.5
  • Pytorch 0.3.1

Training

  • RGB

To train the models, run the script train_rgb.sh, which contains:

python main_rgb.py --dataset gtea_61 --root_dir dataset --outDir experiments --stage 1 \
                   --seqLen 25 --trainBatchSize 32 --numEpochs 200 --lr 0.001 --stepSize 25 75 150 \
                   --decayRate 0.1 --memSize 512 --outPoolSize 100 --evalInterval 5 --split 2

Evaluation

Testing on the trained models can be done by running the script test_rgb.sh

Pretrained models

The pre-trained models can be downloaded from the following Google Drive link

TODO

  1. EPIC-KITCHENS code
  2. Flow and two stream codes
  3. Pre-trained models

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LSTA: Long Short-Term Attention for Egocentric Action Recognition - CVPR 2019

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