This is a caffe repository for transfer learning. We fork the repository with version ID 29cdee7 from Caffe and make our modifications. The main modifications are listed as follow:
- Add
mmd layerdescribed in paper "Learning Transferable Features with Deep Adaptation Networks". - Add
entropy layerandouterproduct layerdescribed in paper "Unsupervised Domain Adaptation with Residual Transfer Networks". - Copy
grl layerandmessenger.hppfrom repository Caffe. - Emit
SOLVER_ITER_CHANGEmessage insolver.cppwheniter_changes.
In data/office/*.txt, we give the lists of three domains in Office dataset.
In models/DAN/amazon_to_webcam, we give an example model based on Alexnet to show how to transfer from amazon to webcam. In this model, we insert mmd layers after fc7 and fc8 individually.
The bvlc_reference_caffenet is used as the pre-trained model. If the Office dataset and pre-trained caffemodel is prepared, the example can be run with the following command:
"./build/tools/caffe train -solver models/DAN/amazon_to_webcam/solver.prototxt -weights models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel"
In mmd-layer, parameter loss_weight can be tuned to give mmd loss different weights.
@inproceedings{DBLP:conf/icml/LongC0J15,
author = {Mingsheng Long and
Yue Cao and
Jianmin Wang and
Michael I. Jordan},
title = {Learning Transferable Features with Deep Adaptation Networks},
booktitle = {Proceedings of the 32nd International Conference on Machine Learning,
{ICML} 2015, Lille, France, 6-11 July 2015},
pages = {97--105},
year = {2015},
crossref = {DBLP:conf/icml/2015},
url = {http://jmlr.org/proceedings/papers/v37/long15.html},
timestamp = {Tue, 12 Jul 2016 21:51:15 +0200},
biburl = {http://dblp2.uni-trier.de/rec/bib/conf/icml/LongC0J15},
bibsource = {dblp computer science bibliography, http://dblp.org}
}