README.md

Unsupervised Deep Hashing with Fine-grained Similarity-preserving Contrastive Learning for Image Retrieval

This is the implementation of paper: Unsupervised Deep Hashing with Fine-grained Similarity-preserving Contrastive Learning for Image Retrieval

the Framework of the Proposed FSCH

Datasets

Experiments on 4 image datasets: CIFAR-10，FLICKR25K, NUS-WIDE, MS COCO

Datasets Download

#	Datasets	Download
1	CIFAR-10	Link
2	FLICKR25K	Link
3	NUS-WIDE	Link
4	MS COCO	Link

Pretrained Model

You can download pre-trained models: ViT-B/L-16/32 here.

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Citation

If you find the code in this repository useful for your research consider citing it.

@article{cao2023FSCH,
title={Unsupervised Deep Hashing with Fine-grained Similarity-preserving Contrastive Learning for Image Retrieval},
journal = {IEEE Transactions on Circuits and Systems for Video Technology}​，
author={Hu Cao, Lei Huang, Jie Nie, Zhiqiang Wei},
year={2023}
}