Skip to content

yabufarha/ms-tcn

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation

This repository provides a PyTorch implementation of the paper MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation.

An extended version has been published in TPAMI Link.

Tested with:

  • PyTorch 0.4.1
  • Python 2.7.12

Qualitative Results:

IMAGE ALT TEXT

Training:

  • Download the data folder, which contains the features and the ground truth labels. (~30GB) (If you cannot download the data from the previous link, try to download it from here)
  • Extract it so that you have the data folder in the same directory as main.py.
  • To train the model run python main.py --action=train --dataset=DS --split=SP where DS is breakfast, 50salads or gtea, and SP is the split number (1-5) for 50salads and (1-4) for the other datasets.

Prediction:

Run python main.py --action=predict --dataset=DS --split=SP.

Evaluation:

Run python eval.py --dataset=DS --split=SP.

Citation:

If you use the code, please cite

Y. Abu Farha and J. Gall.
MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation.
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019

S. Li, Y. Abu Farha, Y. Liu, MM. Cheng,  and J. Gall.
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation.
In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages