Skip to content
Branch: master
Find file History
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information. add: MRAN code Sep 2, 2019 add: MRAN code Sep 2, 2019 add: MRAN code Sep 2, 2019 add: MRAN code Sep 2, 2019


A PyTorch implementation of 'Multi-representationadaptationnetworkforcross-domainimage classification'. The contributions of this paper are summarized as follows.

  • We are the first to learn multiple different domain-invariant representations by Inception Adaptation Module (IAM) for cross-domain image classification.
  • A novel Multi-Representation Adaptation Network (MRAN) is proposed to align distributions of multiple different representations which might contain more information about the images.


  • python 3
  • pytorch 0.3.1
  • torchvision 0.2.0


  1. You can download Office31 dataset here. And then unrar dataset in ./dataset/.
  2. You can change the source_name and target_name in to set different transfer tasks.
  3. Run python

Results on Office31

Method A - W D - W W - D A - D D - A W - A Average
MRAN 91.4±0.1 96.9±0.3 99.8±0.2 86.4±0.6 68.3±0.5 70.9±0.6 85.6


Zhu Y, Zhuang F, Wang J, et al. Multi-representation adaptation network for cross-domain image classification[J]. Neural Networks, 2019.


If you have a problem with the code, please contact

You can’t perform that action at this time.