The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Similarity Reasoning and Filtration for Image-Text Matching
Open accessAbstract
Image-text matching plays a critical role in bridging the vision and language, and great progress has been made by exploiting the global alignment between image and sentence, or local alignments between regions and words. However, how to make the most of these alignments to infer more accurate matching scores is still underexplored. In this paper, we propose a novel Similarity Graph Reasoning and Attention Filtration (SGRAF) network for image-text matching. Specifically, the vector-based similarity representations are firstly learned to characterize the local and global alignments in a more comprehensive manner, and then the Similarity Graph Reasoning (SGR) module relying on one graph convolutional neural network is introduced to infer relation-aware similarities with both the local and global alignments. The Similarity Attention Filtration (SAF) module is further developed to integrate these alignments effectively by selectively attending on the significant and representative alignments and meanwhile casting aside the interferences of non-meaningful alignments. We demonstrate the superiority of the proposed method with achieving state-of-the-art performances on the Flickr30K and MSCOCO datasets, and the good interpretability of SGR and SAF with extensive qualitative experiments and analyses.
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Cited by
Huang, S.-C., Shen, L., Lungren, M. P., & Yeung, S. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00391 · Cited by 489
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Self-citationVision-Language Pre-Training: Basics, Recent Advances, and Future Trends
Gan, Z., Li, L., Li, C., Wang, L., Liu, Z., & Gao, J. (2022) · Foundations and Trends® in Computer Graphics and Vision · doi:10.1561/0600000105 · Cited by 155
AI-assisted automated scoring of picture-cued writing tasks for language assessment
Zhao, R., Zhuang, Y., Zou, D., Xie, Q., & Yu, P. L. H. (2023) · Education and Information Technologies · doi:10.1007/s10639-022-11473-y · Cited by 40
Metadata
- Authors
- Diao, H., Zhang, Y., Ma, L., & Lu, H.
- Venue
- Proceedings of the AAAI Conference on Artificial Intelligence
- Published
- 2021-05-18
- Volume
- 35
- Issue
- 2
- Pages
- 1218-1226
- ISSN
- 2159-5399 (ISSN-L)
- 2374-3468
- OpenAlex
- W3118694826
- Cited by
- 361
- References
- 48
- FWCI
- 21.74
- Type
- conference paper
- Language
- en
- Open access
- diamond
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- Diao, H., Zhang, Y., Ma, L., & Lu, H. (2021). Similarity Reasoning and Filtration for Image-Text Matching. Proceedings of the AAAI Conference on Artificial Intelligence. https://doi.org/10.1609/aaai.v35i2.16209
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