This Git contains trained models of MixDCNN for three fine-grained datasets, CUB200-2011 (http://www.vision.caltech.edu/visipedia/CUB-200-2011.html), Birdsnap (http://birdsnap.com/) and CLEF-FLower (http://www.imageclef.org/datasets). Training and testing split files are provided for all three datasets.
This repository maintains links to MixDCNN caffe models used in the following paper:
@inproceedings{GeWACV2016,
author = {ZongYuan Ge and Alex Bewley and Christopher McCool and Ben Upcroft and Peter Corke and Conrad Sanderson},
title = {Fine-Grained Classification via Mixture of Deep Convolutional Neural Networks},
booktitle = {Winter Conference on the Applications of Computer Vision (WACV)},
publisher = {IEEE},
year = {2016}
}
The caffemodel weights for the best performing models can be downloaded from the links below:
![Result Table] https://github.com/zongyuange/MixDCNN/blob/master/result.png
Please visit https://sites.google.com/view/zongyuange/home for details, or visit http://arma.sourceforge.net/vb100/ if you are interested in bird video dataset.