The DOI matches its Crossref record; 38 of the 40 references it cites were found in a registry or an index.
Multimodal Convolutional Neural Networks for Matching Image and Sentence
Abstract
In this paper, we propose multimodal convolutional neural networks (m-CNNs) for matching image and sentence. Our m-CNN provides an end-to-end framework with convolutional architectures to exploit image representation, word composition, and the matching relations between the two modalities. More specifically, it consists of one image CNN encoding the image content and one matching CNN modeling the joint representation of image and sentence. The matching CNN composes different semantic fragments from words and learns the inter-modal relations between image and the composed fragments at different levels, thus fully exploit the matching relations between image and sentence. Experimental results demonstrate that the proposed m-CNNs can effectively capture the information necessary for image and sentence matching. More specifically, our proposed m-CNNs significantly outperform the state-of-the-art approaches for bidirectional image and sentence retrieval on the Flickr8K and Flickr30K datasets.
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“An adaptive multimodal mapping between two visual modalities (e.g., images and sentences) typically requires strong representations of the individual modalities [213].”
From A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets (2022) · cites this paper as [213]
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A survey on deep learning for multimodal data fusion
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Metadata
- Authors
- Ma, L., Lu, Z., Shang, L., & Li, H.
- Affiliations
- Huawei Technologies (China) (CN)
- Venue
- 2015 IEEE International Conference on Computer Vision (ICCV)
- Publisher
- IEEE
- Published
- 2015-12
- Pages
- 2623-2631
- OpenAlex
- W1916445035
- Cited by
- 334
- References
- 40
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 15 · 2023: 23 · 2022: 29 · 2021: 31 · 2020: 59 · 2019: 67 · 2018: 41 · 2017: 34 · 2016: 18 · 2015: 3
- FWCI
- 13.12
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE/CVF International Conference on Computer Vision (ICCV) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Keywords
- multimodal convolutional neural network, image retrieval, sentence retrieval, cross-modal matching, word composition, Flickr8k, Flickr30k
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