This is our implementation (plus a demo) of CNN feature visualization (Zeiler & Fergus, 2013).
The way to just look at the ipython notebook. Use link: http://nbviewer.ipython.org/github/guruucsd/CNN_visualization/blob/master/urban_tribe/caffe/deconv_demo.ipynb
The visualization result is not as clear as the paper shows. We assume it's because they use different architecture and we have a small dataset for visualization. However, it may due to undetected bugs (but we hope not..) If you find any mistakes in this code, please tell us!
Zeiler, M. D. and Fergus, R. (2013) Visualizing and Understanding Convolutional Networks.
http://arxiv.org/abs/1311.2901
This notebook should be run from the guru2.ucsd.edu
server. Installation of caffe can be quite challenging, and this notebook depends on a particular urban_tribes
model that only exists on that server.
To run,
ssh -X [username@]guru2.ucsd.edu
- Clone this repository
- Run
ipython notebook
and open theCNN_visualization/urban_tribe/caffe/deconv_demo.ipynb
file from the browser.