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Cross-modal Retrieval with Correspondence Autoencoder
Proceedings of the 22nd ACM international conference on Multimedia, 2014The problem of cross-modal retrieval, e.g., using a text query to search for images and vice-versa, is considered in this paper. A novel model involving correspondence autoencoder (Corr-AE) is proposed here for solving this problem. The model is constructed by correlating hidden representations of two uni-modal autoencoders.
Fangxiang Feng, Xiaojie Wang, Ruifan Li
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Audiovisual cross-modal material surface retrieval
Neural Computing and Applications, 2019Cross-modal retrieval is developed rapidly because it can process the data among different modalities. Aiming at solving the problem that the text and image sometimes cannot perform the true and accurate analysis of the material, a system of audiovisual cross-modal retrieval on material surface is proposed.
Zhuokun Liu +4 more
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Correspondence Autoencoders for Cross-Modal Retrieval
ACM Transactions on Multimedia Computing, Communications, and Applications, 2015This article considers the problem of cross-modal retrieval, such as using a text query to search for images and vice-versa. Based on different autoencoders, several novel models are proposed here for solving this problem. These models are constructed by correlating hidden representations of a pair of autoencoders.
Fangxiang Feng +3 more
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Hashing for Cross-Modal Similarity Retrieval
2015 11th International Conference on Semantics, Knowledge and Grids (SKG), 2015Now, cross-modal retrieval similarity on multimedia with texts and images have attracted scholars' more and more attention. The difficulty of cross-modal retrieval is how to effectively construct correlation between multi-modal heterogeneous data. According to canonical correlation analysis, most existing cross-modal methods embed the heterogeneous ...
Yao Liu +3 more
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Random Online Hashing for Cross-Modal Retrieval
IEEE Transactions on Neural Networks and Learning SystemsIn the past decades, supervised cross-modal hashing methods have attracted considerable attentions due to their high searching efficiency on large-scale multimedia databases. Many of these methods leverage semantic correlations among heterogeneous modalities by constructing a similarity matrix or building a common semantic space with the collective ...
Kaihang Jiang +5 more
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Multi-hop Interactive Cross-Modal Retrieval
2019Conventional representation learning based cross-modal retrieval approaches always represent the sentence with a global embedding feature, which easily neglects the local correlations between objects in the image and phrases in the sentence. In this paper, we present a novel Multi-hop Interactive Cross-modal Retrieval Model (MICRM), which interactively
Xuecheng Ning +2 more
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Region-based Cross-modal Retrieval
2022 International Joint Conference on Neural Networks (IJCNN), 2022Danyang Hou +4 more
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Cross-Modality Person Retrieval with Cross-Modality Loss Functions
2023Qing Dong +5 more
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Semantics Consistent Adversarial Cross-Modal Retrieval
2019Cross-modal retrieval returns the relevant results from the other modalities given a query from one modality. The main challenge of cross-modal retrieval is the “heterogeneity gap” amongst modalities, because different modalities have different distributions and representations.
Ruisheng Xuan +6 more
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