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Graph Convolutional Multi-modal Hashing for Flexible Multimedia Retrieval
ACM Multimedia, 2021Multi-modal hashing makes an important contribution to multimedia retrieval, where a key challenge is to encode heterogeneous modalities into compact hash codes.
Xu Lu +4 more
semanticscholar +1 more source
AToMiC: An Image/Text Retrieval Test Collection to Support Multimedia Content Creation
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023This paper presents the AToMiC (Authoring Tools for Multi media Content) dataset, designed to advance research in image/text cross-modal retrieval.
Jheng-Hong Yang +6 more
semanticscholar +1 more source
Efficient Multi-modal Hashing with Online Query Adaption for Multimedia Retrieval
ACM Trans. Inf. Syst., 2021Multi-modal hashing supports efficient multimedia retrieval well. However, existing methods still suffer from two problems: (1) Fixed multi-modal fusion.
Lei Zhu +5 more
semanticscholar +1 more source
Multimedia information retrieval
ACM SIGIR Forum, 2005The Multimedia Information Retrieval workshop at SIGIR'05 was well attended with about 28 participants. The workshop format consisted of 8 papers on a variety of different topics from features and representations for image retrieval to a complete retrieval system for media monitoring. The list of papers may be seen at http://mmis.doc.ic.ac.uk/mmir2005/,
R Manmatha +2 more
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Fast Discrete Collaborative Multi-Modal Hashing for Large-Scale Multimedia Retrieval
IEEE Transactions on Knowledge and Data Engineering, 2020Many achievements have been made on learning to hash for uni-modal and cross-modal retrieval. However, it is still an unsolved problem that how to directly and efficiently learn discriminative discrete hash codes for the multimedia retrieval, where both ...
Chaoqun Zheng +5 more
semanticscholar +1 more source

