There are two main limitations for existing models: (1) learning of cross-modal representations is restricted to batches; (2) semantically similar samples may be wrongly treated as negative. In this paper, we propose a novel category-level contrastive learning for unsupervised cross-modal hashing,...
Peng Hu, Hongyuan Zhu, Jie Lin, Dezhong Peng, Yin-Ping Zhao, Xi Peng*,Unsupervised Contrastive Cross-modal Hashing, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 3, pp. 3877-3889, 1 March 2023, doi: 10.1109/TPAMI.2022.3177356. (PyTorch Code) ...
Unsupervised cross-modal hashing retrievalContrastive learningAdversarial learningCross-modal ranking learningDynamic optimizationCross-modal hashing encodes multimodal data into a common binary space, which can efficiently measure correlations between cross-modal instances. However, most existing cross-modal ...
Although the fact that current methods have some effects, unsupervised cross-modal hashing methods still face several common challenges. First of all, the
另,如果有其他idea很好的跨模态论文,希望你在文章后面留言! Cross-modal Retrieval 一般一个跨模态检索过程可以既包括模态表征,模态转换,模态对齐和联合学习(唯独没有模态融合,基本上不需要融合)。 Adversarial C... Contrastive Adaptation Network for Unsupervised Domain Adaptation...