Implementation of Exploring hierarchical information in hyperbolic space for self-supervised image hashing
| dataset | class_num | label type | source |
| ImageNet | 100 | single | source# |
| COCO | 80 | multi | source# |
| NUS-WIDE | 21 | multi | source# |
| NIRFlickr-25K | 24 | multi | source |
| VOC2012 | 20 | multi | source |
| CIFAR-10 | 10 | single | source |
python main.py --hyper_c 0.1 --data_name imagenet --data_path xxxx --lambda_q 0.01 --lr 0.0001 --hash_bit 64 --batch_size 64 --R 1000 --start_eval 40 --eval_epochs 2 --epochs 60 --cluster_num 1500,1000,800 --HIC --HPC@ARTICLE{HHCH2024TIP,
author={Wei, Rukai and Liu, Yu and Song, Jingkuan and Xie, Yanzhao and Zhou, Ke},
journal={IEEE Transactions on Image Processing},
title={Exploring Hierarchical Information in Hyperbolic Space for Self-Supervised Image Hashing},
year={2024},
volume={33},
number={},
pages={1768-1781},
doi={10.1109/TIP.2024.3371358}}