Cited by 1,402Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval TechniquesImage Retrieval and Classification Techniques

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 access

Lee, Kuang-Huei, Chen, Xi, Hua, Gang, Hu, Houdong, He, Xiaodong·2018·Lecture Notes in Computer Science

DOI 10.1007/978-3-030-01225-0_13

Open this paper in CoChat — free account Open PDF

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

Crossref · 10.1007/978-3-030-01225-0_13

Cites

41 of 41 references verified0 citation errors · 0 not checkable

Statistics

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

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

Show all 45 references

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

Sorted by citations

Items 801–900 of 1,001

Multiscale Matching Driven by Cross-Modal Similarity Consistency for Audio-Text Retrieval
Wang, Q., Gu, J.-C., & Ling, Z.-H. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10446302 · Cited by 6
Robust Fault Diagnostics of Industrial Motors: The Signal-to-Image Approaches for Sensor Data Using Multi-Task Transformers with Diverse Attention Mechanism
Mukhopadhyay, S., Kar, I., & Ralte, Z. (2024) · International Conference on Control, Instrumentation, Energy & Communication · doi:10.1109/ciec59440.2024.10468531 · Cited by 5
Learning with Noisy Correspondence
Huang, Z., Hu, P., Niu, G., Xiao, X., Lv, J., & Peng, X. (2024) · International Journal of Computer Vision · doi:10.1007/s11263-024-02064-0 · Cited by 5
A Lightweight Multi-Grained Image-Text Retrieval Paradigm via Cascaded Representation Learning and Parameter-Free Feature Aggregation
Lu, C., Zhang, N., & Sun, S. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3443097 · Cited by 5
Multimodal Encoders for Food-Oriented Cross-Modal Retrieval
Ying, C., Zhou, D. M., Li, L., & Han, J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-85899-5_19 · Cited by 5
An animated picture says at least a thousand words: Selecting Gif-based Replies in Multimodal Dialog
Wang, X., & Jurgens, D. (2021) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2021.findings-emnlp.276 · Cited by 5
Cross-modal alignment with graph reasoning for image-text retrieval
Cui, Z., Hu, Y., Sun, Y., Gao, J., & Yin, B. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12444-8 · Cited by 5
Improving text-image cross-modal retrieval with contrastive loss
Zhang, C., Yang, Y., Guo, J., Jin, G., Song, D., & Liu, A. A. (2022) · Multimedia Systems · doi:10.1007/s00530-022-00962-2 · Cited by 5
Video Sampled Frame Category Aggregation and Consistent Representation for Cross-Modal Retrieval
Jin, M., Zhang, H., Zhu, L., Sun, J., & Liu, L. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3204623 · Cited by 5
Relation-Guided Network for Image-Text Retrieval
Yang, Y., Shen, H., & Yang, M. (2022) · Proceedings - International Conference on Image Processing · doi:10.1109/icip46576.2022.9897238 · Cited by 5
RFE-SRN: Image-text similarity reasoning network based on regional feature enhancement
Yang, X., Li, C., Zheng, D., Wen, P. P., & Yin, G. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.11.003 · Cited by 5
VL-NMS: Breaking Proposal Bottlenecks in Two-stage Visual-language Matching
Zhang, C., Ma, W., Xiao, J., Zhang, H., Shao, J., Zhuang, Y., & Chen, L. (2023) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3579095 · Cited by 5
Improving Visual-Semantic Embedding with Adaptive Pooling and Optimization Objective
Zhang, Z., Shu, C., Xiao, Y., Shen, Y., Zhu, D., Chen, Y., Xiao, J., Lau, J. H., Zhang, Q., & Lu, Z. (2023) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.18653/v1/2023.eacl-main.87 · Cited by 5
Fully-attentive iterative networks for region-based controllable image and video captioning
Cornia, M., Baraldi, L., Tal, A., & Cucchiara, R. (2023) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2023.103857 · Cited by 5
Boon: A Neural Search Engine for Cross-Modal Information Retrieval
Gong, Y., & Cosma, G. (2023) · doi:10.1145/3606040.3617440 · Cited by 6
Discourse Component to Sentence (DC2S): An Efficient Human-Aided Construction of Paraphrase and Sentence Similarity Dataset
Cho, W. I., Kim, J. I., Moon, Y. K., & Kim, N. S. (2020) · Language Resources and Evaluation · Cited by 5
Multi-modal Label Retrieval for the Visual Arts: The Case of Iconclass
Banar, N., Daelemans, W. M. P., & Kestemont, M. (2021) · International Conference on Agents and Artificial Intelligence (ICAART) · doi:10.5220/0010390606220629 · Cited by 5
Multi-scale Multi-modal Dictionary BERT For Effective Text-image Retrieval in Multimedia Advertising
Yu, T., Liu, J., Jin, Z., Yang, Y., Fei, H., & Li, P. (2022) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3511808.3557653 · Cited by 5
ImaginE: An Imagination-Based Automatic Evaluation Metric for Natural Language Generation
Zhu, W., Wang, X. E., Yan, A., Eckstein, M. P., & Wang, W. Y. (2023) · Findings of the Association for Computational Linguistics: EACL · doi:10.18653/v1/2023.findings-eacl.6 · Cited by 6
Semantic Text-to-Face GAN -ST^2FGPreprint
Oza, M., Chanda, S., & Doermann, D. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.10756 · Cited by 5
Show, Translate and Tell
Peri, D., Sah, S., & Ptucha, R. (2019) · 2019 IEEE International Conference on Image Processing (ICIP) · doi:10.1109/icip.2019.8802922 · Cited by 4
Fine-Grained Alignment and Interaction for Video Grounding With Cross-Modal Semantic Hierarchical Graph
Ran, R., Wei, J., He, S., Zhou, Y., Wang, P., Yang, Y., & Shen, H. T. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3575957 · Cited by 5
MG-KG: Unsupervised video anomaly detection based on motion guidance and knowledge graph
Sun, Q., Yang, Y., Xu, H., Li, Z., Liu, Y., & Wang, H. (2025) · Image and Vision Computing · doi:10.1016/j.imavis.2025.105644 · Cited by 4
Cross-Modality Consistency Network for Remote Sensing Text-Image Retrieval
Sha, Y., Feng, Y., He, M., Jin, Y., You, S., Ji, Y., Wu, F., Liu, S., & Che, S. (2025) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2025.3586914 · Cited by 4
NAC: Mitigating Noisy Correspondence in Cross-Modal Matching Via Neighbor Auxiliary Corrector
Li, Y., Huang, H., Xu, J., & Huang, S. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10448059 · Cited by 4
Rebalanced Vision-Language Retrieval Considering Structure-Aware Distillation
Yang, Y., Xi, W., Zhou, L., & Tang, J. (2024) · IEEE Transactions on Image Processing · doi:10.1109/tip.2024.3518759 · Cited by 4
Multi-Hop Attention Diffusion Graph Neural Networks For Multimodal Fake News Detection
Huang, Z., Lu, D., & Sha, Y. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10887755 · Cited by 4
Diagnostic Captioning by Cooperative Task Interactions and Sample-Graph Consistency
Wang, Z., Wang, L., Li, X., & Zhou, L. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3562866 · Cited by 4
Dual dynamic transformer for image captioning
Shan, C., Song, C., Zou, T., Li, J., & Liu, S. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128597 · Cited by 4
GPO++: A dynamic pooling routing network based on pooling operator for cross-modal retrieval
Zhong, F., Bing, C., & Zhang, S. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128723 · Cited by 4
Prototype-Guided Multilayer Alignment Network for Few-Shot Object Detection in Remote Sensing
Azeem, A., Li, Z., Siddique, A., Zhang, Y., & Li, Y. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3587389 · Cited by 6
VisualRAG: Knowledge-Guided Retrieval Augmentation for Image-Text Matching
Wang, H., Liu, L., Zhang, H., Zhu, L., Chang, X., & Du, H. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3597097 · Cited by 4
DH-Set: Improving Vision-Language Alignment with Diverse and Hybrid Set-Embeddings Learning
Zhang, K., Li, J., Li, Z., & Zhou, S. (2025) · 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/cvpr52734.2025.02327 · Cited by 4
A Comprehensive Review of Multimodal Visual Representation Learning: Tracing the Evolution from CNNs to Transformers and Beyond
Zhang, D., Wong, W. K., & Chew, I. M. (2025) · International Journal of Multimedia Information Retrieval · doi:10.1007/s13735-025-00382-8 · Cited by 5
Enhancing image-text matching through contextual fine-grained alignment
Meng, F., Han, D., Shen, X., Chen, C., & Wang, Q. (2025) · The Visual Computer · doi:10.1007/s00371-025-04250-8 · Cited by 4
Exploring Hierarchical Cross-Modal Correlation Consistency for Partial Mismatching
Liu, X., Yu, Z., Yu, J., Zeng, H., Wang, Z., & Chen, C. L. P. (2026) · IEEE Transactions on Image Processing · doi:10.1109/tip.2026.3666793 · Cited by 4
Aligning Information Capacity Between Vision and Language via Dense-to-Sparse Feature Distillation for Image-Text Matching
Liu, Y., Feng, W., Liu, Z., Huang, & Lv, J. (2025) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51701.2025.02013 · Cited by 4
LLM-Enhanced Action-Aware Multi-Modal Prompt Tuning for Image-Text Matching
Tian, M., Wu, X., & Yang, S. (2025) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51701.2025.01929 · Cited by 4
A Channel Mix Method for Fine-Grained Cross-Modal Retrieval
Shen, Y., Sun, X., Wei, X.-S., Hu, H., & Chen, Z. (2022) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme52920.2022.9859609 · Cited by 4
Self-citation
Cross-modal retrieval of remote sensing images and text based on self-attention unsupervised deep common feature space
Ding, Q., Zhang, H., Wang, X., & Li, W. (2023) · International Journal of Remote Sensing · doi:10.1080/01431161.2023.2225705 · Cited by 4
Dynamic Network for Language-based Fashion Retrieval
Li, H., Wu, Y., & Wang, F. (2023) · doi:10.1145/3606040.3617438 · Cited by 4
Cross-Modal Semantic Alignment Learning for Text-Based Person Search
Gan, W., Liu, J., Zhu, Y., Wu, Y. W., Zhao, G., & Zha, Z.-J. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-53305-1_16 · Cited by 4
Cycle mapping with adversarial event classification network for fake news detection
Wu, F., Zhou, H., Feng, Y., Gao, G., Ji, Y., & Jing, X. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-18499-z · Cited by 4
ITContrast: contrastive learning with hard negative synthesis for image-text matching
Wu, F., Wang, Q., Wang, Z., Yu, S., Li, Y., Zhang, B., & Lim, E. G. (2024) · The Visual Computer · doi:10.1007/s00371-024-03274-w · Cited by 4
Improving Face Recognition from Caption Supervision with Multi-Granular Contextual Feature Aggregation
Hasan, M. M., & Nasrabadi, N. M. (2023) · IEEE International Joint Conference on Biometrics (IJCB) · doi:10.1109/ijcb57857.2023.10448749 · Cited by 4
An end-to-end image-text matching approach considering semantic uncertainty
Tuerhong, G., Dai, X., Tian, L., & Wushouer, M. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128386 · Cited by 4
Bias Mitigation and Representation Optimization for Noise-Robust Cross-Modal Retrieval
Liu, Y., Chen, H., Qin, G., Song, J., & Yang, X. (2024) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3700596 · Cited by 4
Image-text Retrieval with Main Semantics Consistency
Xie, Y., Wang, Y., Xie, Y., Tan, X., Li, J., Li, X., Peng, W., Tang, M., & Fang, M. (2024) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3627673.3679619 · Cited by 4
Object-Aware Query Perturbation for Cross-Modal Image-Text Retrieval
Sogi, N., Shibata, T., & Terao, M. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72986-7_26 · Cited by 4
PointCloud-Text Matching: Benchmark Dataset and Baseline
Feng, Y., Qin, Y., Peng, D., Zhu, H., Peng, X., & Hu, P. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3590931 · Cited by 5
Multi-model Network for Fine-Grained Cross-Media Retrieval
Bai, J., Yao, Y., Wang, Q., Zhou, Y., Yang, W., & Shen, F. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-60639-8_16 · Cited by 4
Efficient Fine-Grained Visual-Text Search Using Adversarially-Learned Hash Codes
Li, Y., Mu, Y., Zhuang, N., & Liu, X. (2021) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme51207.2021.9428271 · Cited by 4
Incorporating Concreteness in Multi-Modal Language Models with Curriculum Learning
Sezerer, E., & Tekır, S. (2021) · Applied Sciences · doi:10.3390/app11178241 · Cited by 5
Self-Attention based fine-grained cross-media hybrid network
Shan, W., Huang, D., Wang, J., Zou, F., & Li, S. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108748 · Cited by 4
BI-LSTM Based Encoding and GAN for Text-to-Image Synthesis
Talasila, V., & Narasingarao, M. R. (2022) · Sensing and Imaging · doi:10.1007/s11220-022-00390-6 · Cited by 4
Texture BERT for Cross-modal Texture Image Retrieval
Xu, Z., Yu, T., & Li, P. (2022) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3511808.3557710 · Cited by 4
Fast unsupervised consistent and modality-specific hashing for multimedia retrieval
Yang, Z., Deng, X., & Long, J. (2022) · Neural Computing and Applications · doi:10.1007/s00521-022-08008-4 · Cited by 4
NewsStories: Illustrating Articles with Visual Summaries
Tan, R., Plummer, B. A., Saenko, K., Lewis, J. P., Sud, A., & Leung, T. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20059-5_37 · Cited by 4
Selective Progressive Learning for Sparse Depth Completion
Liang, X., & Jung, C. (2022) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr56361.2022.9956621 · Cited by 4
Multimodal Content Veracity Assessment with Bidirectional Transformers and Self-Attention-based Bi-GRU Networks
Wang, J., Norouzi, M., & Tsai, S. M. (2022) · IEEE International Conference on Multimedia Big Data · doi:10.1109/bigmm55396.2022.00030 · Cited by 4
Image-text matching using multi-subspace joint representation
Sun, H., Qin, X., & Liu, X. (2023) · Multimedia Systems · doi:10.1007/s00530-022-01038-x · Cited by 4
Scene-Centric vs. Object-Centric Image-Text Cross-Modal Retrieval: A Reproducibility Study
Hendriksen, M., Vakulenko, S., Kuiper, E., & de Rijke, M. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-28241-6_5 · Cited by 4
Multi-scale motivated neural network for image-text matching
Qin, X., Li, L., & Pang, G. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-15321-0 · Cited by 4
Using Multiple Instance Learning to Build Multimodal Representations
Wang, P., Wells, W. M., Berkowitz, S., Horng, S., & Golland, P. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-34048-2_35 · Cited by 4
SCCS: Semantics-Consistent Cross-domain Summarization via Optimal Transport Alignment
Qiu, J., Zhu, J., Xu, M., Dernoncourt, F., Bui, T., Wang, Z., Li, B., Zhao, D. X., & Jin, H. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.101 · Cited by 4
Cross‐Shape Attention for Part Segmentation of 3D Point Clouds
Loizou, M., Garg, S., Petrov, D. A., Averkiou, M., & Kalogerakis, E. (2023) · Computer Graphics Forum · doi:10.1111/cgf.14909 · Cited by 4
Multi-Modal Representation Learning with Text-Driven Soft Masks
Park, J., & Han, B. (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/cvpr52729.2023.00274 · Cited by 6
An approach for devising stenography application using cross modal attention
Jananee, V., Shanthalakshmi, M., Mishra, S., Samuel, L. J., Prabakar, R., & Shalini, M. (2023) · AIP conference proceedings · doi:10.1063/5.0152434 · Cited by 4
A Texture and Saliency Enhanced Image Learning Method For Cross-Modal Remote Sensing Image-Text Retrieval
Yang, R., Zhang, D., Guo, Y., & Wang, S. (2023) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss52108.2023.10282896 · Cited by 4
Few-Shot Common Action Localization via Cross-Attentional Fusion of Context and Temporal Dynamics
Lee, J., Jain, M., & Yun, S. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00937 · Cited by 4
CoVLR: Coordinating Cross-Modal Consistency and Intra-Modal Relations for Vision-Language Retrieval
Wan, F., Wu, X., Guan, Z., & Yang, Y. (2024) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme57554.2024.10688342 · Cited by 4
Semantic Modeling of Textual Relationships in Cross-modal Retrieval
Yu, J., Yang, C., Qin, Z., Yang, Z., Hu, Y., & Shi, Z. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-29551-6_3 · Cited by 4
Exploring Entity-Level Spatial Relationships for Image-Text Matching
Xia, Y., Huang, L., Wang, W., Wei, X.-Y., & Chen, J. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054758 · Cited by 4
mmFilter
Hu, Z., Ye, N., Phillips, C., Capes, T., & Mohomed, I. (2020) · International Middleware Conference · doi:10.1145/3429357.3430518 · Cited by 4
Advancing weakly supervised cross-domain alignment with optimal transport
Yuan, S., Bai, K., Chen, L., Zhang, Y., Tao, C., Li, C., Wang, G., Henao, R., & Duke, L. C. (2020) · British Machine Vision Conference (BMVC) · doi:10.5244/c.34.139 · Cited by 4
An Unsupervised Sampling Approach for Image-Sentence Matching Using Document-level Structural Information
Li, Z., Wei, Z., Fan, Z., Shan, H., & Huang, X. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i15.17573 · Cited by 4
Fine-Grained Cross-Modal Retrieval for Cultural Items with Focal Attention and Hierarchical Encodings
Sheng, S., Laenen, K., Gool, L. V., & Moens, M. (2021) · Computers · doi:10.3390/computers10090105 · Cited by 4
Inter-Modality Fusion Based Attention for Zero-Shot Cross-Modal Retrieval
Chakraborty, B., Wang, P., & Wang, L. (2021) · Proceedings - International Conference on Image Processing · doi:10.1109/icip42928.2021.9506182 · Cited by 4
Local Self-Attention on Fine-grained Cross-media Retrieval
Wang, C., Yao, Y., Wang, Q., & Tang, Z. (2021) · ACM International Conference on Multimedia in Asia (MMAsia) · doi:10.1145/3469877.3490590 · Cited by 4
Learning cross-modality features for image caption generation
Zeng, C., & Kwong, S. (2022) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-022-01506-w · Cited by 4
A Multi-source Heterogeneous Data Storage and Retrieval System for Intelligent Manufacturing
Kong, Y., Li, D., Li, C., Chu, D., & Yao, Z. (2021) · IEEE International Conference on e-Business Engineering (ICEBE) · doi:10.1109/icebe52470.2021.00032 · Cited by 4
Multi-level network based on transformer encoder for fine-grained image–text matching
Yang, L., Feng, Y., Zhou, M., Xiong, X., Wang, Y., & Qiang, B. (2023) · Multimedia Systems · doi:10.1007/s00530-023-01079-w · Cited by 4
Scene Graph based Fusion Network for Image-Text Retrieval
Wang, G., Shang, Y., Chen, Y., Zhen, C., & Cheng, D. (2023) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme55011.2023.00032 · Cited by 4
Text Matters but Speech Influences: A Computational Analysis of Syntactic Ambiguity ResolutionPreprint
Cho, W. I., Cho, J., Kang, W. H., & Kim, N. S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.09275 · Cited by 4
Natural Language for Human-Robot Collaboration: Problems Beyond Language GroundingPreprint
Pate, S., Xu, W., Yang, Z., Love, M., Ganguri, S., & Wong, L. L. S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.04441 · Cited by 5
Deep Multimodal Image-Text Embeddings for Automatic Cross-Media RetrievalPreprint
Khojasteh, H. A., Ansari, E., Razzaghi, P., & Karimi, A. (2020) · HAL · doi:10.48550/arxiv.2002.10016 · Cited by 4
"It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models
Garg, K., Tang, X., Heo, J., Morgan, D. R., Gergle, D., Sudderth, E. B., & Piper, A. M. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791309 · Cited by 3
“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.”
A hyperparameter-free Scene-Motion Aware Cross Attention Network for video anomaly detection in surveillance
Sun, Q., Yang, Y., Liu, Y., & Wang, H. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.130348 · Cited by 3
A Unified Generative Hashing for Cross-Modal Retrieval
Tu, J., Liu, X., Hao, Y., & Hong, R. (2025) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3744567 · Cited by 4
Benchmark Granularity and Model Robustness for Image-Text Retrieval: A Reproducibility Study
Hendriksen, M., Zhang, S., Reinanda, R., Yahya, M., Meij, E., & de Rijke, M. (2025) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3726302.3730290 · Cited by 3
Multi-scale Feature Refinement via Perspective Scaling and Adaptive Regularization for text-based person search
Xie, S., Zhang, C., Ma, R., Li, Z., Wang, Z., & Wei, C. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111496 · Cited by 3
Visual Semantic Contextualization Network for Multi-Query Image Retrieval
Ji, Z., Li, Z., Zhang, Y., Pang, Y., & Li, X. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3590927 · Cited by 3
DADA++: Dual Alignment Domain Adaptation for Unsupervised Video-Text Retrieval
Hao, X., Diao, Y., Yin, R., Yin, R., Zhang, J., Zhang, J., & Zhou, W. (2025) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3759252 · Cited by 3
Beyond One and Two Tower: Cross-Modal Consensus Learning for Image-Text Retrieval
Shi, Z., Ding, Y., Dong, J., & Zhang, T. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3605958 · Cited by 3
VTLG: A vision-tactile-language grasp generation method oriented towards task
Li, T., Yu, C., Yan, Y., Song, D., Shuai, Y., Wang, Y., & Chen, G. (2025) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2025.103152 · Cited by 4
PUMA: Layer-Pruned Language Model for Efficient Unified Multimodal Retrieval with Modality-Adaptive Learning
Lyu, Y., Shao, R., Chen, G., Zhu, Y., Guan, W., & Nie, L. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3755029 · Cited by 6
Neighborhood-interference independent graph mechanisms for image-text matching
Li, B., Li, Z., Wu, Y., & Wei, X. (2026) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-025-02818-3 · Cited by 1
A data-efficient foundation model for porous materials based on expert-guided supervised learning
Zou, J., Lv, Z., Tan, W., Wang, T., Lin, R., Wang, Z., Yang, Y., Li, Q., Li, X., Yan, B., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-69245-y · Cited by 4
Distribution-to-Points Matching for Image Text Retrieval
Wang, Z., Xu, X., Zhu, L., Song, J., Yang, Y., & Shen, H. T. (2026) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2026.3664613 · Cited by 3
ReCoTR: Reducing Semantic Cognitive Shift via Dual-Consensus Token Compression for Remote Sensing Image-Text Retrieval
Huang, J., Chen, Y., Du, C., Xiong, S., & Lu, X. (2026) · IEEE Transactions on Image Processing · doi:10.1109/tip.2026.3690309 · Cited by 3

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
ORCID: Chen, Xi
Hua, Gang
He, Xiaodong
Venue: Lecture Notes in Computer Science
Publisher: Springer International Publishing
Published: 2018
Pages: 212-228
ISSN: 0302-9743 (ISSN-L)
1611-3349
DOI: 10.1007/978-3-030-01225-0_13
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
Licence: www.springer.com/tdm (tdm)
www.springer.com/tdm (vor)
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

Stacked Cross Attention for Image-Text Matching

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks