内容提示: Multi-Label Cross-modal RetrievalViresh Ranjan 1∗ Nikhil Rasiwasia 2 C. V. Jawahar 31 Virginia Tech 2 Snapdeal.com 3 CVIT, IIIT HyderabadAbstractIn this work, we address the problem of cross-modal re-trieval in presence of multi-label annotations. In particu-lar, we ...
This leads to a more challenging task of multi-label cross-modal retrieval in which multiple concepts are annotated as labels for images as an example. More importantly, the co-occurrence patterns of concepts result in correlated pairs of labels whose relationships need to be considered in an ...
journal={IEEE Transactions on Circuits and Systems for Video Technology}, title={Deep Semantic-Aware Proxy Hashing for Multi-Label Cross-Modal Retrieval}, year={2024}, volume={34}, number={1}, pages={576-589}, doi={10.1109/TCSVT.2023.3285266}}...
Cross-modal retrieval tasks can be regarded as the extension of a single-modal retrieval task. Its purpose is to bridge the relationship among different modalities. Given one of these modalities as inputs, the retrieval system outputs all related data from other modalities. For instance, we use...
). Cross-modal retrieval systems previously relied on single-label multimodal data sources; however, several multi-label data sets with multiple modalities have recently been introduced. Multi-label datasets consider introducing a natural many-to-many interaction across different methods; i.e., each ...
The recent deep cross-modal hashing (DCMH) has achieved superior performance in effective and efficient cross-modal retrieval and thus has drawn increasing attention. Nevertheless, there are still two limitations for most existing DCMH methods: (1) single labels are usually leveraged to measure the...
The recent deep cross-modal hashing (DCMH) has achieved superior performance in effective and efficient cross-modal retrieval and thus has drawn increasing attention. Nevertheless, there are still two limitations for most existing DCMH methods: (1) single labels are usually leveraged to measure the...
Cross-media Retrieval (关于跨模态检索的概念、方法、主要挑战和开放性问题,包括数据集和实验结果的基准) 主要挑战:media gap 不同模态的表示特征不一致并且位于不同的特征空间中,主要挑战是度量它们之间的相似性。 当前...共同空间。 大多数现有方法仅用于检索两种媒体类型(主要是图像和文本),但跨模态检索强调媒体...
Cross-modal retrieval has gained much attention due to the growing demand for enormous multi-modal data in recent years (i.e., image-text or text-image ret... Y Jian,J Xiao,Y Cao,... - IEEE International Conference on Multimedia & Expo 被引量: 0发表: 2019年 Missing multi-label learn...
Cross-modal discrete hashing Pattern Recognit. (2018) LuoY.et al. Robust discrete code modeling for supervised hashing Pattern Recognit. (2018) MaQ.et al. Supervised learning based discrete hashing for image retrieval Pattern Recognit. (2019) ...