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DeepJDOT

This repository contains the codes of the following paper

BB Damodaran, B Kellenberger, R Flamary, D Tuia, N Courty, "DeepJDOT:Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation", in European Conference on Computer Vision 2018 (ECCV-2018).

Dependencies

In order to run, the code requires the following Python modules:

  • Numpy
  • Matplotlib
  • POT (Python Optimal Transport library)
  • keras with tensorflow backend

Modules

  • Deepjdot - module contains the implementation of the DeepJDOT
  • dnn - import necessary functions from keras
  • deepjdot_demo - DeepJDOT on the sample dataset

To run the DeepJDOT on the sample dataset, Please see or run the "deepjdot_demo.py"

To run on the real data set: SVHN --> MNIST, please see "deepjdot_svhn_mnist.py"

deepjdot's People

Contributors

bbdamodaran avatar offchan42 avatar

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