Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval
Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval 解决问题：1.在模型训练时利用单标签去估计语义相关性，但实际数据集中有多类标签同时存在，利用多标签更精准；2.利用哈希编码会导致高维数据的丢失 主要思想：自监督对抗哈希网络 将标签作为自监督学习的标准，建立两个对抗网络，可让文本，图像，标签在特征提取后信息丢
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相关文章
- 1. Binary Generative Adversarial Networks for Image Retrieval
- 2. Deep Supervised Hashing for Fast Image Retrieval
- 3. Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval
- 4. Hierarchical deep semantic hashing for fast image retrieval
- 5. Instance-Aware Hashing for Multi-Label Image Retrieval 解析
- 6. CartoonGAN: Generative Adversarial Networks for Photo Cartoonization
- 7. Generative Adversarial Networks for Hyperspectral Image Classification
- 8. 论文阅读（6）：Deep Clustering and Block Hashing Network for Face Image Retrieval
- 9. 跨模态检索Triplet Fusion Network Hashing for Unpaired Cross-Modal Retrieval
- 10. Deep Semantic Hashing with Generative Adversarial Networks 论文review（翻译）