The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
CAMP: Cross-Modal Adaptive Message Passing for Text-Image Retrieval
Open accessAbstract
Text-image cross-modal retrieval is a challenging task in the field of language and vision. Most previous approaches independently embed images and sentences into a joint embedding space and compare their similarities. However, previous approaches rarely explore the interactions between images and sentences before calculating similarities in the joint space. Intuitively, when matching between images and sentences, human beings would alternatively attend to regions in images and words in sentences, and select the most salient information considering the interaction between both modalities. In this paper, we propose Cross-modal Adaptive Message Passing (CAMP), which adaptively controls the information flow for message passing across modalities. Our approach not only takes comprehensive and fine-grained cross-modal interactions into account, but also properly handles negative pairs and irrelevant information with an adaptive gating scheme. Moreover, instead of conventional joint embedding approaches for text-image matching, we infer the matching score based on the fused features, and propose a hardest negative binary cross-entropy loss for training. Results on COCO and Flickr30k significantly surpass state-of-the-art methods, demonstrating the effectiveness of our approach.
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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
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Microsoft COCO: Common Objects in Context
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Chung, J., Gulcehre, C., Cho, K., & Bengio, Y. (2014) · arXiv · doi:10.48550/arxiv.1412.3555 · Cited by 11,008
Deep visual-semantic alignments for generating image descriptions
Karpathy, A., & Fei-Fei, L. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298932 · Cited by 4,902
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Stacked Attention Networks for Image Question Answering
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SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning
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Self-citationKnowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning
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Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding
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Stacked Cross Attention for Image-Text Matching
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Cited by
Similarity Reasoning and Filtration for Image-Text Matching
Diao, H., Zhang, Y., Ma, L., & Lu, H. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i2.16209 · Cited by 361
GilBERT: Generative Vision-Language Pre-Training for Image-Text Retrieval
Hong, W., Ji, K., Liu, J., Wang, J., Chen, J., & Chu, W. (2021) · Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3404835.3462838 · Cited by 37
Metadata
- Authors
- Wang, Z., Liu, X., Li, H., Sheng, L., Yan, J., Wang, X., & Shao, J.
- Venue
- 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
- Publisher
- IEEE
- Published
- 2019-10
- Pages
- 5763-5772
- OpenAlex
- W2994818707
- Cited by
- 359
- References
- 34
- FWCI
- 12.65
- Type
- conference paper
- Language
- en
- Open access
- green
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- Wang, Z., Liu, X., Li, H., Sheng, L., Yan, J., Wang, X., & Shao, J. (2019). CAMP: Cross-Modal Adaptive Message Passing for Text-Image Retrieval. 2019 IEEE/CVF International Conference on Computer Vision (ICCV). https://doi.org/10.1109/iccv.2019.00586
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