ParseNet on PASCAL 2012 dataset

This is a model presented in the paper

ParseNet: Looking Wider to See Better
Wei Liu, Andrew Rabinovich, Alexander C. Berg
arXiv:1506.04579

This is the ParseNet model trained on PASCAL (using extra data from Hariharan et al. and finetuned from the fully convolutional reduced VGGNet).

You should be able to train/eval this model with http://github.com/weiliu89/caffe/tree/fcn. This branch introduces filter_stride (used for 'atrous' algorithm as described in Deeplab), L2-norm layer, evaluation code on the fly, etc.

The model should obtain 69.55 mean IoU on PASCAL 2012 segmementation val dataset. Please feel free to send me email (wliu@cs.unc.edu) if you have any questions.