Skip to content
No description, website, or topics provided.
Jupyter Notebook Other
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.
DCTW train [MMI].ipynb
MMI Revised (WP).ipynb

Deep Canonical Time Warping

A Tensorflow implementation of the Deep Canonical Time Warping.

Deep Canonical Time Warping
G. Trigeorgis, M. A. Nicolaou, S. Zafeiriou, B. Schuller.
Proceedings of IEEE International Conference on Computer Vision & Pattern Recognition (CVPR'16).
June 2016.

Installation Instructions

We are an avid supporter of the Menpo project ( which we use in various ways throughout the implementation.

In general, as explained in Menpo's installation instructions, it is highly recommended to use conda as your Python distribution.

Once downloading and installing conda, this project can be installed by:

Step 1: Create a new conda environment and activate it:

$ conda create -n dctw python=3.5
$ source activate dctw

Step 2: Install TensorFlow following the official installation instructions. For example, for 64-bit Linux, the installation of CPU-only, Python 3.5 TensorFlow involves:

(dctw)$ pip install --upgrade

Step 3: Install menpo from the menpo channel as:

(dctw)$ conda install -c menpo menpo

Step 4: Compile the extra TraceNormOp op.

(dctw)$ bash

When you are done you can go through the example in demo.ipynb.

You can’t perform that action at this time.