The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.
On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval
Abstract
The problem of cross-modal retrieval from multimedia repositories is considered. This problem addresses the design of retrieval systems that support queries across content modalities, for example, using an image to search for texts. A mathematical formulation is proposed, equating the design of cross-modal retrieval systems to that of isomorphic feature spaces for different content modalities. Two hypotheses are then investigated regarding the fundamental attributes of these spaces. The first is that low-level cross-modal correlations should be accounted for. The second is that the space should enable semantic abstraction. Three new solutions to the cross-modal retrieval problem are then derived from these hypotheses: correlation matching (CM), an unsupervised method which models cross-modal correlations, semantic matching (SM), a supervised technique that relies on semantic representation, and semantic correlation matching (SCM), which combines both. An extensive evaluation of retrieval performance is conducted to test the validity of the hypotheses. All approaches are shown successful for text retrieval in response to image queries and vice versa. It is concluded that both hypotheses hold, in a complementary form, although evidence in favor of the abstraction hypothesis is stronger than that for correlation.
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Cites
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Cited by
Adversarial Cross-Modal Retrieval
Wang, B., Yang, Y., Xu, X., Hanjalic, A., & Shen, H. T. (2017) · Proceedings of the 25th ACM international conference on Multimedia · doi:10.1145/3123266.3123326 · Cited by 779
Deep Supervised Cross-Modal Retrieval
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An Overview of Cross-Media Retrieval: Concepts, Methodologies, Benchmarks, and Challenges
Peng, Y., Huang, X., & Zhao, Y. (2018) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2017.2705068 · Cited by 341
HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment
Vulić, I., Gerz, D., Kiela, D., Hill, F., & Korhonen, A. (2016) · arXiv · doi:10.48550/arxiv.1608.02117 · Cited by 90
Metadata
- Authors
- Costa Pereira, J., Coviello, E., Doyle, G., Rasiwasia, N., Lanckriet, G. R. G., Levy, R., & Vasconcelos, N.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2014-03
- Volume
- 36
- Issue
- 3
- Pages
- 521-535
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- OpenAlex
- W2138118304
- Cited by
- 435
- References
- 62
- FWCI
- 35.31
- Type
- journal article
- Language
- en
- Open access
- closed
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