zexuanqiu / CIBHash

source code for paper "Unsupervised Hashing with Contrastive Information Bottleneck" published in IJCAI 2021

CIBHash

A Pytorch implementation of paper "Unsupervised Hashing with Contrastive Information Bottleneck "

Main Dependencies

• torch 1.4.0
• torchvision 0.5.0
• Pillow 5.4.1
• opencv-python 4.5.1.48

How to Run

# Run with the Cifar10 dataset
python main.py cifar16 --train --dataset cifar10 --encode_length 16 --cuda

If you run the above command, the program will download the Cifar10 dataset to the directory ./data/cifar10/ and then start to train.

Moreover, you can find the download link of NUS-WIDE dataset in this page; as for the MSCOCO dataset, you can directly visit the homepage to get the source data. You can refer to ./utils/data.py to get hints of preprocessing these two datasets.