Controllable Video Captioning With POS Sequence Guidance Based on Gated Fusion Network
Open accessAbstract
In this paper, we propose to guide the video caption generation with Part-of-Speech (POS) information, based on a gated fusion of multiple representations of input videos. We construct a novel gated fusion network, with one particularly designed cross-gating (CG) block, to effectively encode and fuse different types of representations, e.g., the motion and content features of an input video. One POS sequence generator relies on this fused representation to predict the global syntactic structure, which is thereafter leveraged to guide the video captioning generation and control the syntax of the generated sentence. Specifically, a gating strategy is proposed to dynamically and adaptively incorporate the global syntactic POS information into the decoder for generating each word. Experimental results on two benchmark datasets, namely MSR-VTT and MSVD, demonstrate that the proposed model can well exploit complementary information from multiple representations, resulting in improved performances. Moreover, the generated global POS information can well capture the global syntactic structure of the sentence, and thus be exploited to control the syntactic structure of the description. Such POS information not only boosts the video captioning performance but also improves the diversity of the generated captions. Our code is at: https://github.com/vsislab/Controllable_XGating.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
A multimodal model can aggregate motion, acoustic and temporal information from successive frames to assign a caption to each frame.
“Moreover, a multimodal model can also aggregate motion information [174], acoustic information [175], temporal information [176], etc. from successive frames to assign a caption for each one.”
From A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets (2022) · cites this paper as [174]
Cites
ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380 · see citing works
BLEU: a method for automatic evaluation of machine translation
Papineni, K., Roukos, S., Ward, T., & Zhu, W.-J. (2001) · Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02 · doi:10.3115/1073083.1073135 · Cited by 21,344 · see citing works
(2004) · Cited by 9,718 · see citing works
Learning Spatiotemporal Features with 3D Convolutional Networks
Tran, D., Bourdev, L., Fergus, R., Torresani, L., & Paluri, M. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.510 · Cited by 9,593 · see citing works
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
Carreira, J., & Zisserman, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.502 · Cited by 9,570 · see citing works
ADADELTA: An Adaptive Learning Rate Method
Zeiler, M. D. (2012) · arXiv · doi:10.48550/arxiv.1212.5701 · Cited by 5,322 · see citing works
Long-term recurrent convolutional networks for visual recognition and description
Donahue, J., Hendricks, L. A., Guadarrama, S., Rohrbach, M., Venugopalan, S., Darrell, T., & Saenko, K. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298878 · Cited by 5,228 · see citing works
CIDEr: Consensus-based image description evaluation
Vedantam, R., Zitnick, C. L., & Parikh, D. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7299087 · Cited by 4,845 · see citing works
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Szegedy, C., Ioffe, S., Vanhoucke, V., & Alemi, A. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v31i1.11231 · Cited by 4,636 · see citing works
(2005) · Cited by 4,152 · see citing works
The Kinetics Human Action Video DatasetPreprint
Kay, W., Carreira, J., Simonyan, K., Zhang, B., Hillier, C., Vijayanarasimhan, S., Viola, F., Green, T., Back, T., Natsev, P., et al. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1705.06950 · Cited by 3,711 · see citing works
Bleu: a method for automatic evaluation of machine translation
Papineni, K. (2024) · doi:10.57702/ljteqmrb · Cited by 3,682 · see citing works
Feature-rich part-of-speech tagging with a cyclic dependency network
Toutanova, K., Klein, D., Manning, C. D., & Singer, Y. (2003) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.3115/1073445.1073478 · Cited by 2,889 · see citing works
ActivityNet: A large-scale video benchmark for human activity understanding
Heilbron, F. C., Escorcia, V., Ghanem, B., & Niebles, J. C. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298698 · Cited by 2,578 · see citing works
Self-Critical Sequence Training for Image Captioning
Rennie, S. J., Marcheret, E., Mroueh, Y., Ross, J., & Goel, V. (2017) · 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/cvpr.2017.131 · Cited by 2,177 · see citing works
MSR-VTT: A Large Video Description Dataset for Bridging Video and Language
Xu, J., Mei, T., Yao, T., & Rui, Y. (2016) · 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/cvpr.2016.571 · Cited by 1,810 · see citing works
The kinetics human action video dataset
Kay, W. (2024) · TIB Data Manager · doi:10.57702/jtuxnt5m · Cited by 1,646 · see citing works
Microsoft COCO Captions: Data Collection and Evaluation Server
Chen, X., Fang, H., Lin, T.-Y., Vedantam, R., Gupta, S., Dollar, P., & Zitnick, C. L. (2015) · arXiv · doi:10.48550/arxiv.1504.00325 · Cited by 1,614 · see citing works
Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding
Fukui, A., Park, D. H., Yang, D., Rohrbach, A., Darrell, T., & Rohrbach, M. (2016) · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d16-1044 · Cited by 1,582 · see citing works
Sequence to Sequence -- Video to Text
Venugopalan, S., Rohrbach, M., Donahue, J., Mooney, R., Darrell, T., & Saenko, K. (2015) · IEEE International Conference on Computer Vision · doi:10.1109/iccv.2015.515 · Cited by 1,507 · see citing works
Describing Videos by Exploiting Temporal Structure
Yao, L., Torabi, A., Cho, K., Ballas, N., Pal, C., Larochelle, H., & Courville, A. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.512 · Cited by 1,035 · see citing works
Wang, J., Zhang, T., Song, J., Sebe, N., & Shen, H. T. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2699960 · Cited by 1,034 · see citing works
Self-citationTranslating Videos to Natural Language Using Deep Recurrent Neural Networks
Venugopalan, S., Xu, H., Donahue, J., Rohrbach, M., Mooney, R. J., & Saenko, K. (2015) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.3115/v1/n15-1173 · Cited by 996 · see citing works
Collecting Highly Parallel Data for Paraphrase Evaluation
Chen, D. J., & Dolan, W. B. (2011) · Cited by 898 · see citing works
Hadamard Product for Low-rank Bilinear PoolingPreprint
Kim, J.-H., On, K.-W., Lim, W., Kim, J., Ha, J.-W., & Zhang, B. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1610.04325 · Cited by 604 · see citing works
Jointly Modeling Embedding and Translation to Bridge Video and Language
Pan, Y., Mei, T., Yao, T., Li, H., & Rui, Y. (2016) · 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/cvpr.2016.497 · Cited by 573 · see citing works
Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks
Yu, H., Wang, J., Huang, Z., Yang, Y., & Xu, W. (2016) · 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/cvpr.2016.496 · Cited by 568 · see citing works
Self-citationGuadarrama, S., Krishnamoorthy, N., Malkarnenkar, G., Venugopalan, S., Mooney, R. J., Darrell, T., & Saenko, K. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.337 · Cited by 500 · see citing works
Semantic Compositional Networks for Visual Captioning
Gan, Z., Gan, C., He, X., Pu, Y., Tran, K., Gao, J., Carin, L., & Deng, L. (2017) · 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/cvpr.2017.127 · Cited by 462 · see citing works
Pérez, J. S., Meinhardt-Llopis, E., & Facciolo, G. (2013) · Image Processing On Line · doi:10.5201/ipol.2013.26 · Cited by 417 · see citing works
Das, A., Datta, S., Gkioxari, G., Lee, S., Parikh, D., & Batra, D. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00008 · Cited by 410 · see citing works
Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual GroundingPreprint
Fukui, A., Park, D. H., Yang, D., et al. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1606.01847 · Cited by 388 · see citing works
Translating Video Content to Natural Language Descriptions
Rohrbach, M., Qiu, W., Titov, I., Thater, S., Pinkal, M., & Schiele, B. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.61 · Cited by 384 · see citing works
Video Captioning with Transferred Semantic Attributes
Pan, Y., Yao, T., Li, H., & Mei, T. (2017) · 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/cvpr.2017.111 · Cited by 368 · see citing works
Kojima, A., Tamura, T., & Fukunaga, K. (2002) · International Journal of Computer Vision · doi:10.1023/a:1020346032608 · Cited by 359 · see citing works
Reconstruction Network for Video Captioning
Wang, B., Ma, L., Zhang, W., & Liu, W. (2018) · 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/cvpr.2018.00795 · Cited by 350 · see citing works
Self-citationMultimodal Convolutional Neural Networks for Matching Image and Sentence
Ma, L., Lu, Z., Shang, L., & Li, H. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.301 · Cited by 334 · see citing works
Self-citationXu, R., Xiong, C., Chen, W. R., & Corso, J. J. (2015) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v29i1.9512 · Cited by 309 · see citing works
Recurrent Fusion Network for Image Captioning
Jiang, W., Ma, L., Jiang, Y., Liu, W., & Zhang, T. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01216-8_31 · Cited by 303 · see citing works
Self-citationDas, A., Datta, S., Gkioxari, G., Lee, S., Parikh, D., & Batra, D. (2018) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2018.00279 · Cited by 288 · see citing works
Learning to Answer Questions from Image Using Convolutional Neural Network
Ma, L., Lu, Z., & Li, H. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v30i1.10442 · Cited by 260 · see citing works
Self-citationFeng, Y., Ma, L., Liu, W., & Luo, J. (2019) · 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/cvpr.2019.00425 · Cited by 234 · see citing works
Self-citationBidirectional Attentive Fusion with Context Gating for Dense Video Captioning
Wang, J., Jiang, W., Ma, L., Liu, W., & Xu, Y. (2018) · 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/cvpr.2018.00751 · Cited by 231 · see citing works
Self-citationLess Is More: Picking Informative Frames for Video Captioning
Chen, Y., Wang, S., Zhang, W., & Huang, Q. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01261-8_22 · Cited by 222 · see citing works
Self-citationCoherent Multi-sentence Video Description with Variable Level of Detail
Rohrbach, A., Rohrbach, M., Qiu, W., Friedrich, A., Pinkal, M., & Schiele, B. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-11752-2_15 · Cited by 209 · see citing works
Quantization-based hashing: a general framework for scalable image and video retrieval
Song, J., Gao, L., Liu, L., Zhu, X., & Sebe, N. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.03.021 · Cited by 183 · see citing works
Learning Multimodal Attention LSTM Networks for Video Captioning
Xu, J., Yao, T., Zhang, Y., & Mei, T. (2017) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3123266.3123448 · Cited by 180 · see citing works
M3: Multimodal Memory Modelling for Video Captioning
Wang, J., Wang, W., Huang, Y., Wang, L., & Tan, T. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00784 · Cited by 159 · see citing works
Self-citationSibNet: Sibling Convolutional Encoder for Video Captioning
Liu, S., Ren, Z., & Yuan, J. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1145/3240508.3240667 · Cited by 151 · see citing works
Motion Guided Spatial Attention for Video Captioning
Chen, S., & Jiang, Y. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33018191 · Cited by 134 · see citing works
Ramanishka, V., Das, A., Park, D. H., Venugopalan, S., Hendricks, L. A., Rohrbach, M., & Saenko, K. (2016) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2964284.2984066 · Cited by 132 · see citing works
Describing Videos using Multi-modal Fusion
Jin, Q., Chen, J., Chen, S., Xiong, Y., & Hauptmann, A. G. (2016) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2964284.2984065 · Cited by 104 · see citing works
Regularizing RNNs for Caption Generation by Reconstructing the Past with the Present
Chen, X., Ma, L., Jiang, W., Yao, J., & Liu, W. (2018) · 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/cvpr.2018.00834 · Cited by 96 · see citing works
Self-citationFrame- and Segment-Level Features and Candidate Pool Evaluation for Video Caption Generation
Shetty, R., & Laaksonen, J. T. (2016) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2964284.2984062 · Cited by 88 · see citing works
Reconstruct and Represent Video Contents for Captioning via Reinforcement Learning
Zhang, W., Wang, B., Ma, L., & Liu, W. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2920899 · Cited by 83 · see citing works
Self-citationImage Caption Generation with Part of Speech Guidance
He, X., Shi, B., Bai, X., Xia, G.-S., Zhang, Z., & Dong, W. (2017) · Pattern Recognition Letters · doi:10.1016/j.patrec.2017.10.018 · Cited by 78 · see citing works
Video Captioning with Guidance of Multimodal Latent Topics
Chen, S., Chen, J., Jin, Q., & Hauptmann, A. G. (2017) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3123266.3123420 · Cited by 67 · see citing works
Interpretable Video Captioning via Trajectory Structured Localization
Wu, X., Li, G., Cao, Q., Ji, Q., & Lin, L. (2018) · 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/cvpr.2018.00714 · Cited by 61 · see citing works
Reconstruction Network for Video CaptioningPreprint
Wang, B., Ma, L., Zhang, W., et al. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1803.11438 · Cited by 40 · see citing works
Self-citationBidirectional Attentive Fusion with Context Gating for Dense Video CaptioningPreprint
Wang, J., Jiang, W., Ma, L., et al. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1804.00100 · Cited by 39 · see citing works
Self-citationMatching Image and Sentence with Multi-faceted Representations
Ma, L., Jiang, W., Jie, Z., Jiang, Y., & Liu, W. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2916167 · Cited by 30 · see citing works
Self-citationHierarchical Photo-Scene Encoder for Album Storytelling
Wang, B., Ma, L., Zhang, W., Jiang, W., & Zhang, F. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33018909 · Cited by 29 · see citing works
Self-citationRegularizing RNNs for Caption Generation by Reconstructing The Past with The PresentPreprint
Chen, X., Ma, L., Jiang, W., et al. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1803.11439 · Cited by 27 · see citing works
Self-citationLess Is More: Picking Informative Frames for Video CaptioningPreprint
Chen, Y., Wang, S., Zhang, W., et al. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1803.01457 · Cited by 26 · see citing works
Self-citationDiverse and Controllable Image Captioning with Part-of-Speech GuidancePreprint
Deshpande, A., Aneja, J., Wang, L., Schwing, A. G., & Forsyth, D. A. (2018) · arXiv (Cornell University) · Cited by 12 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Bayoudh, K., Knani, R., Hamdaoui, F., & Mtibaa, A. (2022) · The Visual Computer · doi:10.1007/s00371-021-02166-7 · Cited by 456 · see citing works
Object Relational Graph With Teacher-Recommended Learning for Video Captioning
Zhang, Z., Shi, Y., Yuan, C., Li, B., Wang, P., Hu, W., & Zha, Z.-J. (2020) · 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/cvpr42600.2020.01329 · Cited by 342 · see citing works
SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning
Lin, K., Li, L., Lin, C.-C., Ahmed, F., Gan, Z., Liu, Z., Lu, Y., & Wang, L. (2022) · 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/cvpr52688.2022.01742 · Cited by 321 · see citing works
Spatio-Temporal Graph for Video Captioning With Knowledge Distillation
Pan, B., Cai, H., Huang, D.-A., Lee, K.-H., Gaidon, A., Adeli, E., & Niebles, J. C. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.01088 · Cited by 281 · see citing works
Syntax-Aware Action Targeting for Video Captioning
Zheng, Q., Wang, C., & Tao, D. (2020) · 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/cvpr42600.2020.01311 · Cited by 211 · see citing works
Temporally Grounding Language Queries in Videos by Contextual Boundary-Aware Prediction
Wang, J., Ma, L., & Jiang, W. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6897 · Cited by 186 · see citing works
Self-citationEnd-to-end Generative Pretraining for Multimodal Video Captioning
Seo, P. H., Nagrani, A., Arnab, A., & Schmid, C. (2022) · 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/cvpr52688.2022.01743 · Cited by 173 · see citing works
TSP: Temporally-Sensitive Pretraining of Video Encoders for Localization Tasks
Alwassel, H., Giancola, S., & Ghanem, B. (2021) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw54120.2021.00356 · Cited by 136 · see citing works
Hierarchical Modular Network for Video Captioning
Ye, H., Li, G., Qi, Y., Wang, S., Huang, Q., & Yang, M. (2022) · 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/cvpr52688.2022.01741 · Cited by 121 · see citing works
Video Captioning Using Global-Local Representation
Yan, L., Ma, S.-Q., Wang, Q., Chen, Y., Zhang, X., Savakis, A., & Liu, D. (2022) · IEEE transactions on circuits and systems for video technology (Print) · doi:10.1109/tcsvt.2022.3177320 · Cited by 106 · see citing works
Open-book Video Captioning with Retrieve-Copy-Generate Network
Zhang, Z., Qi, Z., Yuan, C., Shan, Y., Li, B., Deng, Y., & Hu, W. (2021) · 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/cvpr46437.2021.00971 · Cited by 112 · see citing works
Multimodal research in vision and language: A review of current and emerging trends
Uppal, S., Bhagat, S., Hazarika, D., Majumder, N., Poria, S., Zimmermann, R., & Zadeh, A. (2021) · Information Fusion · doi:10.1016/j.inffus.2021.07.009 · Cited by 112 · see citing works
Gao, L., Yu, L., Zeng, P., Song, J., Wang, M., & Shen, H. T. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3120867 · Cited by 103 · see citing works
Image Captioning With End-to-End Attribute Detection and Subsequent Attributes Prediction
Huang, Y., Chen, J., Ouyang, W., Wan, W., & Xue, Y. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.2969330 · Cited by 102 · see citing works
Large Scale Holistic Video Understanding
Diba, A., Fayyaz, M., Sharma, V., Paluri, M., Gall, J., Stiefelhagen, R., & Gool, L. V. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58558-7_35 · Cited by 106 · see citing works
Long Short-Term Relation Transformer With Global Gating for Video Captioning
Li, L., Gao, X., Deng, J., Tu, Y., Zha, Z.-J., & Huang, Q. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3158546 · Cited by 99 · see citing works
Learning Modality Interaction for Temporal Sentence Localization and Event Captioning in Videos
Chen, S., Jiang, W., Liu, W., & Jiang, Y. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58548-8_20 · Cited by 98 · see citing works
Self-citationText with Knowledge Graph Augmented Transformer for Video Captioning
Gu, X., Chen, G., Wang, Y., Zhang, L., Luo, T., & Wen, L. (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/cvpr52729.2023.01816 · Cited by 98 · see citing works
Syntax-Guided Hierarchical Attention Network for Video Captioning
Deng, J., Li, L., Zhang, B., Wang, S., Zha, Z.-J., & Huang, Q. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3063423 · Cited by 87 · see citing works
Non-Autoregressive Coarse-to-Fine Video Captioning
Yang, B., Zou, Y., Liu, F., & Zhang, C. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i4.16421 · Cited by 87 · see citing works
Motion Guided Region Message Passing for Video Captioning
Chen, S., & Jiang, Y. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00157 · Cited by 80 · see citing works
VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset
Liu, J., Chen, S., He, X., Guo, L., Zhu, X., Wang, W., & Tang, J. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3479776 · Cited by 103 · see citing works
Learning to Discretely Compose Reasoning Module Networks for Video Captioning
Tan, G., Liu, D., Wang, M., & Zha, Z.-J. (2020) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2020/104 · Cited by 68 · see citing works
Tian, Y., Pan, G., & Alouini, M. (2020) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2020.3042630 · Cited by 68 · see citing works
Learning Audio-Video Modalities from Image Captions
Nagrani, A., Seo, P. H., Seybold, B., Hauth, A., Manén, S., Sun, C., & Schmid, C. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19781-9_24 · Cited by 68 · see citing works
GL-RG: Global-Local Representation Granularity for Video Captioning
Yan, L., Wang, Q., Cui, Y., Feng, F., Quan, X., Zhang, X., & Liu, D. (2022) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2022/384 · Cited by 63 · see citing works
SBAT: Video Captioning with Sparse Boundary-Aware Transformer
Jin, T., Huang, S., Chen, M., Li, Y., & Zhang, Z. M. (2020) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2020/88 · Cited by 62 · see citing works
Emotional Video Captioning With Vision-Based Emotion Interpretation Network
Song, P., Guo, D., Yang, X., Tang, S., & Wang, M. (2024) · IEEE Transactions on Image Processing · doi:10.1109/tip.2024.3359045 · Cited by 62 · see citing works
Refined Semantic Enhancement towards Frequency Diffusion for Video Captioning
Zhong, X., Li, Z., Chen, S., Jiang, K., Chen, C., & Ye, M. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i3.25484 · Cited by 59 · see citing works
Relation-aware Instance Refinement for Weakly Supervised Visual Grounding
Liu, Y., Wan, B., Ma, L., & He, X. (2021) · 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/cvpr46437.2021.00556 · Cited by 56 · see citing works
Self-citationA Semantics-Assisted Video Captioning Model Trained With Scheduled Sampling
Chen, H., Lin, K., Maye, A., Li, J., & Hu, X. (2020) · Frontiers in Robotics and AI · doi:10.3389/frobt.2020.475767 · Cited by 54 · see citing works
Towards Knowledge-Aware Video Captioning via Transitive Visual Relationship Detection
Wu, B., Niu, G., Yu, J., Xiao, X., Zhang, J., & Wu, H. R. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3169894 · Cited by 51 · see citing works
Video description: A comprehensive survey of deep learning approaches
Rafiq, G., Rafiq, M. T., & Choi, G. S. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10414-6 · Cited by 51 · see citing works
DeCEMBERT: Learning from Noisy Instructional Videos via Dense Captions and Entropy Minimization
Tang, Z., Lei, J., & Bansal, M. (2021) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2021.naacl-main.193 · Cited by 48 · see citing works
Prompt Learns Prompt: Exploring Knowledge-Aware Generative Prompt Collaboration For Video Captioning
Yan, L., Han, C., Xu, Z., Liu, D., & Wang, Q. (2023) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2023/180 · Cited by 47 · see citing works
Improving Video Captioning with Temporal Composition of a Visual-Syntactic Embedding
Perez-Martin, J., Bustos, B., & Pérez, J. E. P. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00308 · Cited by 45 · see citing works
Stacked Multimodal Attention Network for Context-Aware Video Captioning
Zheng, Y., Zhang, Y., Feng, R., Zhang, T., & Fan, W. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3058626 · Cited by 43 · see citing works
SPT: Spatial Pyramid Transformer for Image Captioning
Zhang, H., Zeng, P., Gao, L., Lyu, X., Song, J., & Shen, H. T. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3336371 · Cited by 41 · see citing works
Concept-Aware Video Captioning: Describing Videos With Effective Prior Information
Yang, B., Cao, M., & Zou, Y. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3307969 · Cited by 39 · see citing works
Learning Hierarchical Modular Networks for Video Captioning
Li, G., Ye, H., Qi, Y., Wang, S., Qing, L., Huang, Q., & Yang, M. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3327677 · Cited by 39 · see citing works
Semantic Relation-aware Difference Representation Learning for Change Captioning
Tu, Y., Yao, T., Li, L., Lou, J., Gao, S., Yu, Z., & Yan, C. C. (2021) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2021.findings-acl.6 · Cited by 38 · see citing works
Knowledge-Based Video Question Answering with Unsupervised Scene Descriptions
García, N., & Nakashima, Y. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58523-5_34 · Cited by 40 · see citing works
Global semantic enhancement network for video captioning
Luo, X., Luo, X., Wang, D., Liu, J., Wan, B., & Zhao, L. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.109906 · Cited by 36 · see citing works
Exploring Video Captioning Techniques: A Comprehensive Survey on Deep Learning Methods
Islam, S., Dash, A., Seum, A., Raj, A. H., Hossain, T., & Shah, F. M. (2021) · SN Computer Science · doi:10.1007/s42979-021-00487-x · Cited by 36 · see citing works
Contextual Attention Network for Emotional Video Captioning
Song, P., Guo, D., Cheng, J. S., & Wang, M. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3183402 · Cited by 36 · see citing works
Visual Commonsense-Aware Representation Network for Video Captioning
Zeng, P., Zhang, H., Gao, L., Li, X., Qian, J., & Shen, H. T. (2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2023.3323491 · Cited by 37 · see citing works
IcoCap: Improving Video Captioning by Compounding Images
Liang, Y., Zhu, L., Wang, X., & Yang, Y. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3322329 · Cited by 35 · see citing works
Neighborhood Contrastive Transformer for Change Captioning
Tu, Y., Li, L., Su, L., Lü, K., & Huang, Q. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3254162 · Cited by 32 · see citing works
A comprehensive review of the video-to-text problem
Perez-Martin, J., Bustos, B., Guimarães, S. J. F., Sipiran, I., Pérez, J. E. P., & Said, G. C. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-021-10104-1 · Cited by 33 · see citing works
Concept Parser With Multimodal Graph Learning for Video Captioning
Wu, B., Liu, B., Huang, P., Bao, J., Peng, X., & Yu, J. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3277827 · Cited by 28 · see citing works
Augmented Partial Mutual Learning with Frame Masking for Video Captioning
Lin, K., Gan, Z., & Wang, L. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i3.16301 · Cited by 26 · see citing works
O2NA: An Object-Oriented Non-Autoregressive Approach for Controllable Video Captioning
Liu, F., Ren, X., Wu, X., Yang, B., Ge, S., & Sun, X. (2021) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2021.findings-acl.24 · Cited by 26 · see citing works
Multi-modal Dependency Tree for Video Captioning
Zhao, W., Wu, X., & Luo, J. (2021) · neural information processing systems · Cited by 25 · see citing works
I2Transformer: Intra- and Inter-Relation Embedding Transformer for TV Show Captioning
Tu, Y., Li, L., Su, L., Gao, S., Yan, C., Zha, Z.-J., Yu, Z., & Huang, Q. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3159472 · Cited by 25 · see citing works
A multi-layer memory sharing network for video captioning
Niu, T.-Z., Dong, S.-S., Chen, Z.-D., Luo, X., Huang, Z. H., Guo, S., & Xu, X.-S. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.109202 · Cited by 25 · see citing works
Attentive Visual Semantic Specialized Network for Video Captioning
Perez-Martin, J., Bustos, B., & Pérez, J. E. P. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9412898 · Cited by 24 · see citing works
Adversarial Reinforcement Learning With Object-Scene Relational Graph for Video Captioning
Hua, X., Xin-qing, W., Rui, T., Shao, F., & Wang, D. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3148868 · Cited by 24 · see citing works
POS-Trends Dynamic-Aware Model for Video Caption
Wang, L., Li, H., Qiu, H., Wu, Q., Meng, F., & Ngan, K. N. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3131721 · Cited by 22 · see citing works
Controllable Video Captioning with an Exemplar Sentence
Yuan, Y., Ma, L., Wang, J., & Zhu, W. (2020) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3394171.3413908 · Cited by 22 · see citing works
Self-citationAligning Source Visual and Target Language Domains for Unpaired Video Captioning
Liu, F., Wu, X., You, C., Ge, S., Zou, Y.-X., & Sun, X. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3132229 · Cited by 37 · see citing works
Style-aware two-stage learning framework for video captioning
Ma, Y.-C., Zhu, Z., Qi, Y.-K., Beheshti, A., Li, Y., Qing, L.-Y., & Li, G.-R. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.112258 · Cited by 21 · see citing works
Identity-Aware Multi-sentence Video Description
Park, J. S., Darrell, T., & Rohrbach, A. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58589-1_22 · Cited by 19 · see citing works
Graph convolutional network meta-learning with multi-granularity POS guidance for video captioning
Li, P., Zhang, P., & Xu, X. (2021) · Neurocomputing · doi:10.1016/j.neucom.2020.12.137 · Cited by 19 · see citing works
Co-Segmentation Aided Two-Stream Architecture for Video Captioning
Vaidya, J., Subramaniam, A., & Mittal, A. (2022) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv51458.2022.00250 · Cited by 19 · see citing works
Exploring deep learning approaches for video captioning: A comprehensive review
Yousif, A. J., & Al-Jammas, M. H. (2023) · e-Prime - Advances in Electrical Engineering Electronics and Energy · doi:10.1016/j.prime.2023.100372 · Cited by 19 · see citing works
Discriminative Style Learning for Cross-Domain Image Captioning
Yuan, J., Zhu, S., Huang, S., Zhang, H., Xiao, Y., Li, Z., & Wang, M. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3145158 · Cited by 19 · see citing works
Bolelli, F., Allegretti, S., & Grana, C. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3055337 · Cited by 18 · see citing works
Confidence Calibration for Deep Renal Biopsy Immunofluorescence Image Classification
Pollastri, F., Maroñas, J., Bolelli, F., Ligabue, G., Paredes, R., Magistroni, R., & Grana, C. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9412685 · Cited by 17 · see citing works
A Multimodal Framework for Video Caption Generation
Bhooshan, R. S., & Suresh, K. (2022) · IEEE Access · doi:10.1109/access.2022.3202526 · Cited by 17 · see citing works
Leveraging Weighted Cross-Graph Attention for Visual and Semantic Enhanced Video Captioning Network
Verma, D., Haldar, A., & Dutta, T. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i2.25343 · Cited by 17 · see citing works
Wajid, M. S., Terashima‐Marín, H., Najafirad, P., Conant-Pablos, S. E., & Wajid, M. A. (2024) · Journal of Open Innovation Technology Market and Complexity · doi:10.1016/j.joitmc.2024.100297 · Cited by 17 · see citing works
Video captioning based on vision transformer and reinforcement learning
Zhao, H. P., Chen, Z., Guo, L., & Han, Z. (2022) · PeerJ Computer Science · doi:10.7717/peerj-cs.916 · Cited by 17 · see citing works
Adaptive Curriculum Learning for Video Captioning
Li, S., Yang, B., & Zou, Y. (2022) · IEEE Access · doi:10.1109/access.2022.3160451 · Cited by 17 · see citing works
Emotion-Oriented Cross-Modal Prompting and Alignment for Human-Centric Emotional Video Captioning
Wang, Y., Liu, Y., Zhou, S., Huang, Y., Tang, C., Zhou, W., & Chen, Z. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3535292 · Cited by 16 · see citing works
Multimodal feature fusion based on object relation for video captioning
Yan, Z., Chen, Y., Song, J., & Zhu, J. (2022) · CAAI Transactions on Intelligence Technology · doi:10.1049/cit2.12071 · Cited by 16 · see citing works
EvCap: Element-Aware Video Captioning
Liu, S., Li, A., Zhao, Y., Wang, J., & Wang, Y. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3399933 · Cited by 16 · see citing works
Self-citationVideo Description: Datasets & Evaluation Metrics
Rafiq, M. T., Rafiq, G., & Choi, G. S. (2021) · IEEE Access · doi:10.1109/access.2021.3108565 · Cited by 16 · see citing works
Variational Stacked Local Attention Networks for Diverse Video Captioning
Deb, T., Sadmanee, A., Bhaumik, K. K., Ali, A. A., Amin, M. A., & Rahman, A. K. M. M. (2022) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv51458.2022.00255 · Cited by 16 · see citing works
The MSR-Video to Text dataset with clean annotations
Chen, H., Li, J., Frintrop, S., & Hu, X. (2022) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2022.103581 · Cited by 16 · see citing works
Cross-Modal Graph With Meta Concepts for Video Captioning
Wang, H., Lin, G., Hoi, S. C. H., & Miao, C. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3192709 · Cited by 15 · see citing works
Interaction augmented transformer with decoupled decoding for video captioning
Jin, T., Zhao, Z., Wang, P., Yu, J., & Wu, F. Q. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.03.065 · Cited by 15 · see citing works
Video captioning: A comparative review of where we are and which could be the route
Moctezuma, D., Ramírez-delReal, T. A., Ruíz, G., & González-Chávez, O. (2023) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2023.103671 · Cited by 14 · see citing works
Semantic guidance network for video captioning
Guo, L., Zhao, H. P., Chen, Z., & Han, Z. (2023) · Scientific Reports · doi:10.1038/s41598-023-43010-3 · Cited by 13 · see citing works
Tang, S., He, P., Li, H., Wang, W., Jiang, X., & Zhao, Y. (2025) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2025.3546845 · Cited by 11 · see citing works
Attention based video captioning framework for Hindi
Singh, A., Singh, T. D., & Bandyopadhyay, S. (2021) · Multimedia Systems · doi:10.1007/s00530-021-00816-3 · Cited by 11 · see citing works
Action-Driven Semantic Representation and Aggregation for Video Captioning
Han, T., Xu, Y., Yu, J., Yu, Z., & Zhao, S. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3502736 · Cited by 10 · see citing works
Dual-Level Decoupled Transformer for Video Captioning
Gao, Y., Hou, X., Suo, W., Sun, M., Ge, T., Jiang, Y., & Wang, P. (2022) · International Conference on Multimedia Retrieval · doi:10.1145/3512527.3531380 · Cited by 10 · see citing works
SEM-POS: Grammatically and Semantically Correct Video Captioning
Nadeem, A., Hilton, A., Dawes, R., Thomas, G., & Mustafa, A. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00259 · Cited by 10 · see citing works
Diverse video captioning through latent variable expansion
Xiao, H., & Shi, J. (2022) · Pattern Recognition Letters · doi:10.1016/j.patrec.2022.05.021 · Cited by 12 · see citing works
Learning distribution of video captions using conditional GAN
Babavalian, M. R., & Kiani, K. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-15933-6 · Cited by 9 · see citing works
Co-segmentation inspired attention module for video-based computer vision tasks
Subramaniam, A., Vaidya, J., Ameen, M., Nambiar, A., & Mittal, A. (2022) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2022.103532 · Cited by 9 · see citing works
CMGNet: Collaborative multi-modal graph network for video captioning
Rao, Q., Yu, X., Li, G., & Zhu, L. (2023) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2023.103864 · Cited by 8 · see citing works
Guide and interact: scene-graph based generation and control of video captions
Lu, X., & Gao, Y. (2022) · Multimedia Systems · doi:10.1007/s00530-022-01012-7 · Cited by 7 · see citing works
Thinking Hallucination for Video Captioning
Ullah, N., & Mohanta, P. P. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26316-3_37 · Cited by 7 · see citing works
Dual Video Summarization: From Frames to Captions
Hu, Z., Wang, Z., Song, Z., & Hong, R. (2023) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2023/94 · Cited by 7 · see citing works
A comprehensive survey on deep-learning-based visual captioning
Xin, B., Xu, N., Zhai, Y., Zhang, T., Lu, Z., Liu, J., Nie, W., Li, X., & Liu, A.-A. (2023) · Multimedia Systems · doi:10.1007/s00530-023-01175-x · Cited by 7 · see citing works
Detecting Multimodal Fake News with Gated Variational AutoEncoder
Gu, Y., Castro, I., & Gareth Tyson, A. (2024) · ACM Web Science Conference (WebSci) · doi:10.1145/3614419.3643992 · Cited by 7 · see citing works
Syntax Customized Video Captioning by Imitating Exemplar Sentences
Yuan, Y., Ma, L., & Zhu, W. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3131618 · Cited by 7 · see citing works
Self-citationReducing 0s bias in video moment retrieval with a circular competence-based captioner
Wang, G., Wu, X., Liu, Z., & Qin, Z. (2022) · Information Processing & Management · doi:10.1016/j.ipm.2022.103147 · Cited by 7 · see citing works
Video Captioning by Learning from Global Sentence and Looking Ahead
Niu, T.-Z., Chen, Z.-D., Luo, X., Zhang, P.-F., Huang, Z. H., & Xu, X.-S. (2023) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3587252 · Cited by 7 · see citing works
- Authors
- Wang, B., Ma, L., Zhang, W., Jiang, W., Wang, J., & Liu, W.
- Affiliations
- Shandong University (CN)
- Tencent (China) (CN)
- Venue
- 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
- Publisher
- IEEE
- Published
- 2019-10
- Pages
- 2641-2650
- OpenAlex
- W2984862483
- Cited by
- 199
- References
- 59
- Citations by year
- 2026: 8 · 2025: 18 · 2024: 22 · 2023: 42 · 2022: 48 · 2021: 45 · 2020: 16
- FWCI
- 8.78
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- IEEE/CVF International Conference on Computer Vision (ICCV) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Tencent
- National Natural Science Foundation of China (2017YFB1300205, 61573222)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Generative Adversarial Networks and Image Synthesis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Analysis and Summarization
- Keywords
- caption diversity, MSR-VTT, MSVD
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
