Awesome

Attend in groups: a weakly-supervised deep learning framework for learning from web data

If you use this code in your research, please cite our paper:

@InProceedings{Zhuang_2017_CVPR,
author = {Zhuang, Bohan and Liu, Lingqiao and Li, Yao and Shen, Chunhua and Reid, Ian},
title = {Attend in Groups: A Weakly-Supervised Deep Learning Framework for Learning From Web Data},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}
}

Dataset

We provide the WebCars dataset here https://mega.nz/file/rZpTVZbD#tleS-mP7XnIO2-_RoxYcO_hUfveURh5XkdGUhQ8fLAM

Code

The code are written using Lasagne.

utils.py: provide necessary functions
vggnet.py: define network structure
train.py: main file, implementing training and testing
config.yaml: define the necessary hyperparameters (e.g., data directory, bag size, GPU), please modify this file
./pretrained_model: the pretrained VGG16 model on ImageNet
img_mean.npy: mean file for data preprocessing

Training

python train.py

Copyright

** This code is for non-commercial purposes only. For commerical purposes, please contact Chunhua Shen chhshen@gmail.com **

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.