Scalable Deep Hashing for Large-Scale Social Image Retrieval
Hui Cui, Lei Zhu, Jingjing Li, Yang Yang, Liqiang Nie
The paper has been published by IEEE Transactions on Image Processing.
url: https://doi.org/10.1109/TIP.2019.2940693
Prerequisites
- Requirements for Caffe, Pycaffe and Matcaffe.
- VGG-16 pre-trained model on ILSVC12 datasets, and save it in caffemodels directory.
Installation
Enter caffe directory and download the source codes.
cd caffe/
Modify Makefile.config and build Caffe with following commands:
make all -j8
make pycaffe
make matcaffe
Usage
We only supply the code to train 32-bit SCADH on MIR Flickr dataset.
We integrate train step and test step in a bash file train32.sh, please run it as follows:
sudo./train32.sh [ROOT_FOLDER] [GPU_ID]
# ROOT_FOLDER is the root folder of image datasets,
# GPU_ID is the GPU you want to train on,
# e.g. sudo ./train32.sh ./flickr_25 1
Citation
If you find our approach useful in your research, please consider citing:
@article{'SCADH',
author = {Hui Cui and Lei Zhu and Jingjing Li and Yang Yang and Liqiang Nie},
journal = {IEEE Transactions on Image Processing (TIP)},
title = {Scalable Deep Hashing for Large-scale Social Image Retrieval},
volume = {29},
pages = {1271-1284},
year = {2020}
}