The DOI matches its Crossref record; 41 of the 45 references it cites were found in a registry or an index.
Stacked Cross Attention for Image-Text Matching
Open accessOverview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Adding images to such measures (e.g., Vilbertscore [72], TIGEr [65], SCAN [75]) or using reference-free measures (e.g., CLIPScore [59]) can help, but degraded images can be a confound in their scores.”
From "It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models (2026) · cites this paper as [75]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Ren, S., He, K., Girshick, R., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2577031 · Cited by 73,472
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Ren, S., He, K., Girshick, R., & Sun, J. (2015) · arXiv · doi:10.48550/arxiv.1506.01497 · Cited by 70,812
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333
Microsoft COCO: Common Objects in Context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.81 · Cited by 32,684
Control of goal-directed and stimulus-driven attention in the brain
Corbetta, M., & Shulman, G. L. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn755 · Cited by 12,881
Bidirectional recurrent neural networks
Schuster, M., & Paliwal, K. K. (1997) · IEEE Transactions on Signal Processing · doi:10.1109/78.650093 · Cited by 10,172
Effective Approaches to Attention-based Neural Machine Translation
Luong, T., Pham, H., & Manning, C. D. (2015) · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d15-1166 · Cited by 8,382
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A., Salakhutdinov, R., Zemel, R., & Bengio, Y. (2015) · arXiv · doi:10.48550/arxiv.1502.03044 · Cited by 8,248
Research works printed but not linked: 6
- Ba, J.L., Kiros, J.R., Hinton, G.E.: Layer normalization. arXiv preprint arXiv:1607.06450 (2016) · arXiv
- Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. In: ICLR (2015)
- Chorowski, J.K., Bahdanau, D., Serdyuk, D., Cho, K., Bengio, Y.: Attention-based models for speech recognition. In: NIPS (2015)
- Faghri, F., Fleet, D.J., Kiros, J.R., Fidler, S.: VSE++: improved visual-semantic embeddings. arXiv preprint arXiv:1707.05612 (2017) · arXiv
- Peng, Y., Qi, J., Yuan, Y.: CM-GANs: cross-modal generative adversarial networks for common representation learning. arXiv preprint arXiv:1710.05106 (2017) · arXiv
- Zheng, Z., Zheng, L., Garrett, M., Yang, Y., Shen, Y.D.: Dual-path convolutional image-text embedding. arXiv preprint arXiv:1711.05535 (2017) · arXiv
Cited by
Sorted by citations
Items 501–600 of 1,001
Multi-task framework based on feature separation and reconstruction for cross-modal retrieval
Zhang, L., & Wu, X. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108217 · Cited by 16
La, T.-V., Dao, M.-S., Tran, Q.-T., Tran, T.-P., Tran, A.-D., & Dang‐Nguyen, D. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3551595 · Cited by 16
Leverage Boosting and Transformer on Text-Image Matching for Cheap Fakes Detection
La, T.-V., Dao, M.-S., Le, D.-D., Phụng, T. K., Nguyen, Q.-H., & Phan-Thi, T.-K. (2022) · Algorithms · doi:10.3390/a15110423 · Cited by 16
A Neighbor-aware Approach for Image-text Matching
Liu, C., Mao, Z., Zang, W., & Wang, B. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8683869 · Cited by 16
From attributes to natural language: A survey and foresight on text-based person re-identification
Jiang, F., Yang, S., Jones, M. W., & Zhang, L. (2025) · Information Fusion · doi:10.1016/j.inffus.2024.102879 · Cited by 18
Quaternion Representation Learning for cross-modal matching
Wang, Z., Xu, X., Wei, J., Xie, N., Shao, J., & Yang, Y. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.110505 · Cited by 15
Consensus Knowledge Exploitation for Partial Query Based Image Retrieval
Zhang, Y., Ji, Z., Pang, Y., & Li, X. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3281507 · Cited by 15
Multi-modal graph contrastive encoding for neural machine translation
Yin, Y., Zeng, J., Su, J., Zhou, C., Meng, F., Zhou, J., Huang, D., & Luo, J. (2023) · Artificial Intelligence · doi:10.1016/j.artint.2023.103986 · Cited by 17
MARN: Multi-level Attentional Reconstruction Networks for Weakly Supervised Video Temporal Grounding
Song, Y., Wang, J., Ma, L., Yu, J., Liang, J., Liu, Y., & Zhou, Y. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126625 · Cited by 15
Are metrics measuring what they should? An evaluation of Image Captioning task metrics
González-Chávez, O., Ruíz, G., Moctezuma, D., & Ramírez-delReal, T. A. (2023) · Signal Processing Image Communication · doi:10.1016/j.image.2023.117071 · Cited by 15
Robust Transformer-based model for spatiotemporal PM$$_{2.5}$$ prediction in California
Tong, W., Limperis, J., Hamza-Lup, F. G., Xu, Y., & Li, L. (2023) · Earth Science Informatics · doi:10.1007/s12145-023-01138-w · Cited by 16
Koyama, K., Hashimoto, K., Nagao, C., & Mizuguchi, K. (2023) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2023.1274599 · Cited by 16
Identification of Necessary Semantic Undertakers in the Causal View for Image-Text Matching
Zhang, H., Zhang, L., Zhang, K., & Mao, Z. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i7.28538 · Cited by 16
A unified multimodal classification framework based on deep metric learning
Peng, L., Jian, S., Li, M., Kan, Z., Qiao, L., & Li, D. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106747 · Cited by 16
Multi-level semantics probability embedding for image–text matching
Liu, A.-A., Yang, L., Li, W., Nie, W., Liu, X., & Chen, H. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2024.103968 · Cited by 15
Review of Recent Deep Learning Based Methods for Image-Text Retrieval
Chen, J., Zhang, L., Bai, C., & Kpalma, K. (2020) · IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR) · doi:10.1109/mipr49039.2020.00042 · Cited by 15
Adversarial Attentive Multi-Modal Embedding Learning for Image-Text Matching
Wei, K., & Zhou, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2996407 · Cited by 15
Image captioning with semantic-enhanced features and extremely hard negative examples
Cai, W., & Liu, Q. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.06.112 · Cited by 15
Combine Early and Late Fusion Together: A Hybrid Fusion Framework for Image-Text Matching
Wang, Y., Xu, X., Yu, W., Xu, R., Cao, Z., & Shen, H. T. (2021) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme51207.2021.9428201 · Cited by 15
Enhancing Descriptive Image Captioning with Natural Language Inference
Shi, Z., Liu, H., & Zhu, X. (2021) · doi:10.18653/v1/2021.acl-short.36 · Cited by 15
Rethinking Label-Wise Cross-Modal Retrieval from A Semantic Sharing Perspective
Yang, Y., Chubing, Z., Xu, Y.-C., Yu, D., Zhan, D., & Yang, J. (2021) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2021/454 · Cited by 15
CANs: Coupled-Attention Networks for Sarcasm Detection on Social Media
Zhao, X., Huang, J. X., & Yang, H. (2021) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn52387.2021.9533800 · Cited by 17
Inflate and Shrink:Enriching and Reducing Interactions for Fast Text-Image Retrieval
Liu, H., Yu, T., & Li, P. (2021) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2021.emnlp-main.772 · Cited by 16
Visual context learning based on textual knowledge for image–text retrieval
Qin, Y., Gu, X., & Tan, Z. (2022) · Neural Networks · doi:10.1016/j.neunet.2022.05.008 · Cited by 15
Heterogeneous memory enhanced graph reasoning network for cross-modal retrieval
Ji, Z., Chen, K., He, Y., Pang, Y., & Li, X. (2022) · Science China Information Sciences · doi:10.1007/s11432-021-3367-y · Cited by 15
Adaptive Latent Graph Representation Learning for Image-Text Matching
Tian, M., Wu, X., & Jia, Y. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3229631 · Cited by 15
Multi-scale image–text matching network for scene and spatio-temporal images
Yu, R., Jin, F., Qiao, Z., Yuan, Y., & Wang, G. (2023) · Future Generation Computer Systems · doi:10.1016/j.future.2023.01.004 · Cited by 15
Bi-Attention enhanced representation learning for image-text matching
Tian, Y., Ding, A., Wang, D., Luo, X., Wan, B., & Wang, Y. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.109548 · Cited by 15
Unsupervised Visual–Textual Correlation Learning With Fine-Grained Semantic Alignment
Peng, Y., Ye, Z., Qi, J., & Zhuo, Y. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.3015084 · Cited by 15
Paired Cross-Modal Data Augmentation for Fine-Grained Image-to-Text Retrieval
Wang, H., Lin, G., Hoi, S. C. H., & Miao, C. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3547809 · Cited by 14
Dual-attention Network for View-invariant Action Recognition
Gedamu, K., Assefa, M., Ayall, T. A., Zhou, C., Liu, H., Seid, A. M., & Erbad, A. (2023) · Complex & Intelligent Systems · doi:10.1007/s40747-023-01171-8 · Cited by 14
MiC: Image-text Matching in Circles with cross-modal generative knowledge enhancement
Pu, X., Chen, Y., Yuan, L., Zhang, Y., Li, H., Jing, L., & Gao, X. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.111503 · Cited by 14
Content Based Deep Learning Image Retrieval: A Survey
Zhang, C., & Liu, J. (2023) · International Conference on Communication and Information Processing (ICCIP) · doi:10.1145/3638884.3638908 · Cited by 14
Hu, J., Chen, K., Rao, B., Ni, J.-Y., Thafar, M. A., Albaradei, S., & Arif, M. (2024) · Analytical Biochemistry · doi:10.1016/j.ab.2024.115637 · Cited by 14
PLOT: Text-Based Person Search with Part Slot Attention for Corresponding Part Discovery
Park, J., Kim, D., Jeong, B., & Kwak, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72664-4_27 · Cited by 14
A reinforcement learning-based approach for solving multi-agent job shop scheduling problem
Dong, Z., Ren, T., Qi, F., Weng, J., Bai, D., Yang, J., & Wu, C. (2024) · International Journal of Production Research · doi:10.1080/00207543.2024.2423807 · Cited by 14
Few-Shot Image and Sentence Matching via Aligned Cross-Modal Memory
Huang, Y., Wang, J., & Wang, L. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3052490 · Cited by 14
Cheng, Q., Zhou, Y., Huang, H., & Wang, Z. (2022) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2022.105773 · Cited by 14
Cross-modal knowledge guided model for abstractive summarization
Wang, H., Liu, J., Duan, M., Gong, P., Wu, Z., Wang, J., & Han, B. (2023) · Complex & Intelligent Systems · doi:10.1007/s40747-023-01170-9 · Cited by 14
Noisy Correspondence Learning with Self-Reinforcing Errors Mitigation
Dang, Z., Luo, M., Jia, C., Dai, G., Chang, X., & Wang, J. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i2.27911 · Cited by 15
Fine-Grained Image-Text Retrieval via Discriminative Latent Space Learning
Zheng, M., Wang, W., & Li, Q. (2021) · IEEE Signal Processing Letters · doi:10.1109/lsp.2021.3065595 · Cited by 14
VD-PCR: Improving visual dialog with pronoun coreference resolution
Yu, X., Zhang, H., Hong, R., Song, Y., & Zhang, C. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108540 · Cited by 15
Remote Sensing Cross-Modal Text-Image Retrieval Based on Attention Correction and Filtering
Yang, X., Li, C., Wang, Z., Xie, H., Mao, J., & Yin, G. (2025) · Remote Sensing · doi:10.3390/rs17030503 · Cited by 13
Diverse Co-Saliency Feature Learning for Text-Based Person Retrieval
You, S., Chen, C., Feng, Y., Liu, H., Ji, Y., & Ye, M. (2025) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2025.3573185 · Cited by 15
From methods to datasets: A survey on Image-Caption Generators
Agarwal, L., & Verma, B. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16560-x · Cited by 16
Yang, R., Wang, S., Zhang, H., Xu, S., Guo, Y., Ye, X., Hou, B., & Jiao, L. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3612207 · Cited by 13
Yang, Y., Guo, J., Li, G., Li, L., Li, W., & Yang, J. J. (2023) · Frontiers of Computer Science · doi:10.1007/s11704-023-3186-6 · Cited by 14
Deep Boosting Learning: A Brand-New Cooperative Approach for Image-Text Matching
Diao, H., Zhang, Y., Gao, S., Ruan, X., & Lu, H. (2024) · IEEE Transactions on Image Processing · doi:10.1109/tip.2024.3396063 · Cited by 13
Global-aware Fragment Representation Aggregation Network for image–text retrieval
Wang, D., Tian, J., Xiao, L., Tian, Y., & He, L. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.111085 · Cited by 13
LP²CR-IoT: Lightweight and Privacy-Preserving Cross-Modal Retrieval in IoT
Li, M., Zhu, Y., Du, R., & Jia, C. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3526939 · Cited by 13
Dynamic Visual Semantic Sub-Embeddings and Fast Re-Ranking for Image-Text Retrieval
Wei, W., Gui, Z., Wu, C., Zhao, A., Peng, D., & Wu, H. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3535373 · Cited by 13
Lang, J., Hong, R., Xu, J., Li, Y., Xu, X., & Zhou, F. (2025) · International World Wide Web Conference (WWW) · doi:10.1145/3696410.3714560 · Cited by 18
A Novel Attention-based Aggregation Function to Combine Vision and Language
Stefanini, M., Cornia, M., Baraldi, L., & Cucchiara, R. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9413269 · Cited by 13
Zero-Shot Compositional Concept Learning
Xu, G., Kordjamshidi, P., & Chai, J. Y. (2021) · doi:10.18653/v1/2021.metanlp-1.3 · Cited by 19
Tops, Bottoms, and Shoes: Building Capsule Wardrobes via Cross-Attention Tensor Network
Chen, H., Lin, Y., Wang, F., & Yang, H. (2021) · ACM Conference on Recommender Systems (RecSys) · doi:10.1145/3460231.3474258 · Cited by 13
Fs-DSM: Few-Shot Diagram-Sentence Matching via Cross-Modal Attention Graph Model
Hu, X., Zhang, L., Liu, J., Zheng, Q., & Zhou, J. J. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3112294 · Cited by 13
Constructing Phrase-level Semantic Labels to Form Multi-Grained Supervision for Image-Text Retrieval
Fan, Z., Wei, Z., Li, Z., Wang, S., Shan, H., Huang, X., & Fan, J. (2022) · International Conference on Multimedia Retrieval · doi:10.1145/3512527.3531368 · Cited by 13
Zhang, H., Sun, Y., Liao, Y., Xu, S., Yang, R., Wang, S., Hou, B., & Jiao, L. (2022) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss46834.2022.9883242 · Cited by 13
NAPReg: Nouns As Proxies Regularization for Semantically Aware Cross-Modal Embeddings
Jawade, B., Mohan, D. D., Ali, N. M., Setlur, S., & Govindaraju, V. (2023) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv56688.2023.00119 · Cited by 13
InfoMetIC: An Informative Metric for Reference-free Image Caption Evaluation
Hu, A., Chen, S., Zhang, L., & Jin, Q. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.178 · Cited by 15
FaD-VLP: Fashion Vision-and-Language Pre-training towards Unified Retrieval and Captioning
Mirchandani, S., Yu, L., Wang, M., Sinha, A., Jiang, W., Xiang, T., & Zhang, N. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.716 · Cited by 13
The Style Transformer With Common Knowledge Optimization for Image-Text Retrieval
Li, W., Ma, Z., Shi, J., & Xiaopeng Fan, B. (2023) · IEEE Signal Processing Letters · doi:10.1109/lsp.2023.3310870 · Cited by 13
TridentCap: Image-Fact-Style Trident Semantic Framework for Stylized Image Captioning
Wang, L., Qiu, H., Qiu, B., Meng, F., Wu, Q., & Li, H. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3315133 · Cited by 13
SignQuery: A Natural User Interface and Search Engine for Sign Languages with Wearable Sensors
Zhou, H., Lu, T., Mckinnie, K., Palagano, J., DeHaan, K., & Gowda, M. (2023) · ACM Annual International Conference on Mobile Computing and Networking (MobiCom) · doi:10.1145/3570361.3613286 · Cited by 13
Contrastive completing learning for practical text–image person ReID: Robuster and cheaper
Du, G., Gong, T., & Zhang, L. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.123399 · Cited by 14
On the Limitations of Visual-Semantic Embedding Networks for Image-to-Text Information Retrieval
Gong, Y., Cosma, G., & Fang, H. (2021) · Journal of Imaging · doi:10.3390/jimaging7080125 · Cited by 15
Multi-modal Learning with Prior Visual Relation Reasoning.Preprint
Yang, Z., Yu, J., Yang, C., Qin, Z., & Hu, Y. (2018) · arXiv (Cornell University) · Cited by 13
Fine-grained multimodal named entity recognition with heterogeneous image-text similarity graphs
Wang, Y., & Jiang, C. (2024) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-024-02398-8 · Cited by 12
Zhang, G., Wei, S., Pang, H., Qiu, S., & Zhao, Y. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3273466 · Cited by 14
Li, J., Xing, Q., Wang, Y., & Chang, Y. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-43412-9_11 · Cited by 12
Xue, J., Wang, Z., Dong, G.-N., & Zhu, A. (2024) · Image and Vision Computing · doi:10.1016/j.imavis.2024.104912 · Cited by 12
Cross-modal Semantic Interference Suppression for image-text matching
Yao, T., Peng, S., Sun, Y., Sheng, G., Fu, H., & Kong, X. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.108005 · Cited by 12
A label information fused medical image report generation framework
Sun, S., Mei, Z., Li, X., Tang, T., Su, Z., & Wu, Y. (2024) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2024.102823 · Cited by 13
Bridging the Cross-Modality Semantic Gap in Visual Question Answering
Wang, B., Ma, Y., Li, X., Gao, J., Hu, Y., & Yin, B. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3370925 · Cited by 13
Multi-Layer Probabilistic Association Reasoning Network for Image-Text Retrieval
Li, W., Xiong, R., & Xiaopeng Fan, B. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3394551 · Cited by 12
Feature-semantic augmentation network for few-shot open-set recognition
Huang, X., & Choi, S. H. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110781 · Cited by 12
Overcoming the Pitfalls of Vision-Language Model for Image-Text Retrieval
Zhang, F., Qu, S., Shi, F., & Xu, C. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3680591 · Cited by 12
Image–Text Matching Model Based on CLIP Bimodal Encoding
Zhu, Y., Xu, H., Du, A., & Wang, B. (2024) · Applied Sciences · doi:10.3390/app142210384 · Cited by 12
Trustworthy Visual-Textual Retrieval
Qin, Y., Huang, L., Peng, D., Jiang, B., Zhou, J. T., Peng, X., & Hu, P. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3587575 · Cited by 12
Cross-modal learning with prior visual relation knowledge
Yu, J., Zhang, W., Yang, Z., Qin, Z., & Hu, Y. (2020) · Knowledge-Based Systems · doi:10.1016/j.knosys.2020.106150 · Cited by 12
Various syncretic co‐attention network for multimodal sentiment analysis
Cao, M., Zhu, Y., Gao, W.-J., Li, M., & Wang, S. (2020) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.5954 · Cited by 12
Hybrid deep neural network for Bangla automated image descriptor
Jishan, M. A., Mahmud, K. R., Azad, A. K. A., Alam, M. S., & Khan, A. M. (2020) · International Journal of Advances in Intelligent Informatics · doi:10.26555/ijain.v6i2.499 · Cited by 12
Cross-modal multi-relationship aware reasoning for image-text matching
Zhang, J., He, X., Qing, L., Liu, L., & Luo, X. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-020-10466-8 · Cited by 12
Self-citationVSR++: Improving Visual Semantic Reasoning for Fine-Grained Image-Text Matching
Yuan, H. L., Huang, Y., Zhang, D., Chen, Z., Cheng, W., & Wang, L. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9413223 · Cited by 12
Softmax Pooling for Super Visual Semantic Embedding
Zeng, Z., Cao, J., Weng, N., Jiang, G., Rao, Y., & Xu, Y. (2021) · IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) · doi:10.1109/iemcon53756.2021.9623131 · Cited by 12
Comprehensive Framework of Early and Late Fusion for Image–Sentence Retrieval
Wang, Y., Xu, X., Yu, W., Xu, R., Cao, Z., & Shen, H. T. (2022) · IEEE Multimedia · doi:10.1109/mmul.2022.3144972 · Cited by 12
Position-aware image captioning with spatial relation
Duan, Y., Wang, Z., Wang, J., Wang, Y., & Lin, C. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.05.003 · Cited by 13
Animating Images to Transfer CLIP for Video-Text Retrieval
Liu, Y., Chen, H., Huang, L., Chen, D., Wang, B., Pan, P., & Wang, L. (2022) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3477495.3531776 · Cited by 13
Chen, Y., Yuan, J., Zhao, L., Chen, T., Luo, R., Davis, L. S., & Metaxas, D. (2023) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv56688.2023.00441 · Cited by 12
Tang, C. Y., Yang, X., Wu, B., Han, Z., & Chang, Y. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00665 · Cited by 12
Feature First: Advancing Image-Text Retrieval Through Improved Visual Features
Wu, D., Li, H., Gu, C., Liu, H., Xu, C., Hou, Y., & Guo, L. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3316077 · Cited by 12
Cross-Modal Person Search: A Coarse-to-Fine Framework using Bi-Directional Text-Image Matching
Yu, X., Chen, T., Yang, Y., Mugo, M., & Wang, Z. (2019) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2019.00223 · Cited by 12
Mind the Remainder: Taylor’s Theorem View on Recurrent Neural Networks
Guan, X., Yang, Y., Li, J., Xu, X., & Shen, H. T. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3042537 · Cited by 12
Dense Contrastive Visual-Linguistic Pretraining
Shi, L., Shuang, K., Geng, S., Gao, P., Fu, Z., de Melo, G., Chen, Y., & Su, S. (2021) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3474085.3475637 · Cited by 12
TIED: A Cycle Consistent Encoder-Decoder Model for Text-to-Image Retrieval
Sebastian, C., Imbriaco, R., Meletis, P., Dubbelman, G., Bondarev, E., & de With, P. H. N. (2021) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw53098.2021.00467 · Cited by 12
PhotoChat: A Human-Human Dialogue Dataset with Photo Sharing Behavior for Joint Image-Text ModelingPreprint
Zang, X., Liu, L., Wang, M., Song, Y., Zhang, H., & Chen, J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.01453 · Cited by 20
A Review of Cross-Modal Image–Text Retrieval in Remote Sensing
Xu, L., Wang, L., Zhang, J., Ha, D., & Zhang, H. (2025) · Remote Sensing · doi:10.3390/rs17243995 · Cited by 13
Multimodal Graph Transformer for Multimodal Question Answering
He, X., & Wang, X. (2023) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.18653/v1/2023.eacl-main.15 · Cited by 16
Self-citationMulti-task hierarchical convolutional network for visual-semantic cross-modal retrieval
Ji, Z., Lin, Z., Wang, H., Pang, Y., & Li, X. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110398 · Cited by 12
Learning to Learn Better Visual Prompts
Wang, F., Huang, W., Yang, S., Fan, Q., & Lan, L. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i6.28343 · Cited by 12
Metadata
- Authors
- Lee, K.-H., Chen, X., Hua, G., Hu, H., & He, X.
- Affiliations
- Microsoft (United States) (US)
- Jingdong (China) (CN)
- Corresponding author
- Lee, Kuang-Huei
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 212-228
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2962964995
- Cited by
- 1,402
- References
- 45
- Citations by year
- 2026: 104 · 2025: 202 · 2024: 244 · 2023: 241 · 2022: 201 · 2021: 211 · 2020: 131 · 2019: 63 · 2018: 5
- FWCI
- 30.89
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- 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
- image-text matching, cross-attention, vision-language alignment, image retrieval, text retrieval, interpretability, MS COCO, Flickr30k
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
