Skip to content

Translating Videos to Commands for Robotic Manipulation with Deep Recurrent Neural Networks - ICRA18

License

Notifications You must be signed in to change notification settings

nqanh/video2command

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

By A Nguyen et al. - ICRA 2018

video2command

Requirements

  • Tensorflow >= 1.0 (used 1.1.0)

Training

  • Clone the repository to your $VC_Folder
  • We train the network using IIT-V2C dataset
  • You can extract the features for each frames in the input videos using any network (e.g., VGG, ResNet, etc.)
  • For a quick start, the pre-extracted features with ResNet50 is available here.
  • Extract the file you downloaded to $VC_Folder/data
  • Start training: python train.py in $VC_Folder/main

Predict & evaluate

  • Predict: python predict.py in $VC_Folder/main folder
  • Prepare the results for evaluation: python prepare_evaluation_format.py in $VC_Folder/evaluation folder
  • Evaluate: python cocoeval.py in $VC_Folder/evaluation folder

If you find this code useful in your research, please consider citing:

@inproceedings{nguyen2018translating,
  title={Translating videos to commands for robotic manipulation with deep recurrent neural networks},
  author={Nguyen, Anh and Kanoulas, Dimitrios and Muratore, Luca and Caldwell, Darwin G and Tsagarakis, Nikos G},
  booktitle={2018 IEEE International Conference on Robotics and Automation (ICRA)},
  year={2018},
  organization={IEEE}
}

Contact

If you have any questions or comments, please send an to anh.nguyen@iit.it

About

Translating Videos to Commands for Robotic Manipulation with Deep Recurrent Neural Networks - ICRA18

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages