11.2.1.3.21 Multimodal, Cross-Modal Visual Sentiment

Chapter Contents (Back)
Visual Sentiment. Multimodal Analysis. Cross-Modal Analysis. Sentiment Analysis.
See also Visual Sentiment Evaluation.
See also Image and Video Memorability.

Zadeh, A., Zellers, R., Pincus, E., Morency, L.P.[Louis-Philippe],
Multimodal Sentiment Intensity Analysis in Videos: Facial Gestures and Verbal Messages,
IEEE_Int_Sys(31), No. 6, November 2016, pp. 82-88.
IEEE DOI 1612
Feature extraction BibRef

Soleymani, M.[Mohammad], Garcia, D.[David], Jou, B.[Brendan], Schuller, B.[Björn], Chang, S.F.[Shih-Fu], Pantic, M.[Maja],
A survey of multimodal sentiment analysis,
IVC(65), No. 1, 2017, pp. 3-14.
Elsevier DOI 1709
Sentiment BibRef

Zhang, X., Gao, X., Lu, W., He, L.,
A Gated Peripheral-Foveal Convolutional Neural Network for Unified Image Aesthetic Prediction,
MultMed(21), No. 11, November 2019, pp. 2815-2826.
IEEE DOI 1911
Feature extraction, Logic gates, Visualization, Convolutional neural networks, Task analysis, Deep learning, deep learning BibRef

Zhang, X., Gao, X., Lu, W., He, L., Li, J.,
Beyond Vision: A Multimodal Recurrent Attention Convolutional Neural Network for Unified Image Aesthetic Prediction Tasks,
MultMed(23), 2021, pp. 611-623.
IEEE DOI 2102
convolutional neural nets, feature extraction, image classification, image enhancement, image fusion, deep learning BibRef

Huang, S., Cornelis, B., Devolder, B., Martens, M., Pizurica, A.,
Multimodal Target Detection by Sparse Coding: Application to Paint Loss Detection in Paintings,
IP(29), 2020, pp. 7681-7696.
IEEE DOI 2007
Sparse representation, target detection, paint loss, kernel, multiple imaging modalities BibRef

Kuang, Q., Jin, X., Zhao, Q., Zhou, B.,
Deep Multimodality Learning for UAV Video Aesthetic Quality Assessment,
MultMed(22), No. 10, October 2020, pp. 2623-2634.
IEEE DOI 2009
Quality assessment, Cameras, Feature extraction, Photography, Drones, Streaming media, Aesthetic quality assessment, deep multimodality learning BibRef

Wen, H.L.[Huang-Lu], You, S.D.[Shao-Di], Fu, Y.[Ying],
Cross-modal context-gated convolution for multi-modal sentiment analysis,
PRL(146), 2021, pp. 252-259.
Elsevier DOI 2105
Artificial neural networks, Affective behavior, Multi-modal temporal sequences BibRef

Wen, H.L.[Huang-Lu], You, S.D.[Shao-Di], Fu, Y.[Ying],
Cross-modal dynamic convolution for multi-modal emotion recognition,
JVCIR(78), 2021, pp. 103178.
Elsevier DOI 2107
Artificial neural networks, Affective behavior, Multi-modal temporal sequences. BibRef

He, J.X.[Jia-Xuan], Mai, S.[Sijie], Hu, H.F.[Hai-Feng],
A Unimodal Reinforced Transformer With Time Squeeze Fusion for Multimodal Sentiment Analysis,
SPLetters(28), 2021, pp. 992-996.
IEEE DOI 2106
Sparse matrices, Sentiment analysis, Fuses, Convolution, Kernel, Analytical models, Visualization, Time squeeze fusion, multimodal sentiment analysis BibRef

Peng, W.[Wei], Hong, X.P.[Xiao-Peng], Zhao, G.Y.[Guo-Ying],
Adaptive Modality Distillation for Separable Multimodal Sentiment Analysis,
IEEE_Int_Sys(36), No. 3, May 2021, pp. 82-89.
IEEE DOI 2107
Tensors, Sentiment analysis, Task analysis, Intelligent systems, Computational modeling, Affective computing, Training data BibRef

Wang, L.J.[Li-Juan], Guo, W.[Wenya], Yao, X.X.[Xing-Xu], Zhang, Y.X.[Yu-Xiang], Yang, J.F.[Ju-Feng],
Multimodal Event-Aware Network for Sentiment Analysis in Tourism,
MultMedMag(28), No. 2, April 2021, pp. 49-58.
IEEE DOI 2107
Feature extraction, Blogs, Sentiment analysis, Visualization, Task analysis, Semantics, Delays BibRef

Xu, N.[Nan], Mao, W.J.[Wen-Ji], Wei, P.H.[Peng-Hui], Zeng, D.[Daniel],
MDA: Multimodal Data Augmentation Framework for Boosting Performance on Sentiment/Emotion Classification Tasks,
IEEE_Int_Sys(36), No. 6, November 2021, pp. 3-12.
IEEE DOI 2112
Task analysis, Data analysis, Boosting, Social networking (online), Annotations, Sentiment analysis, Automation, Data augmentation, multimodal classification BibRef

He, J.X.[Jia-Xuan], Hu, H.F.[Hai-Feng],
MF-BERT: Multimodal Fusion in Pre-Trained BERT for Sentiment Analysis,
SPLetters(29), 2022, pp. 454-458.
IEEE DOI 2202
Bit error rate, Visualization, Acoustics, Sentiment analysis, Analytical models, Fuses, Convolution, Internal updating, multimodal fusion BERT BibRef

Chen, R.[Rongfei], Zhou, W.J.[Wen-Ju], Li, Y.[Yang], Zhou, H.Y.[Hui-Yu],
Video-Based Cross-Modal Auxiliary Network for Multimodal Sentiment Analysis,
CirSysVideo(32), No. 12, December 2022, pp. 8703-8716.
IEEE DOI 2212
Feature extraction, Acoustics, Emotion recognition, Sentiment analysis, Spectrogram, Visualization, Speech recognition, emotion recognition BibRef

Wang, D.[Di], Guo, X.T.[Xu-Tong], Tian, Y.M.[Yu-Min], Liu, J.H.[Jin-Hui], He, L.H.[Li-Huo], Luo, X.M.[Xue-Mei],
TETFN: A text enhanced transformer fusion network for multimodal sentiment analysis,
PR(136), 2023, pp. 109259.
Elsevier DOI 2301
Multimodal sentiment analysis, Transformer, Text-oriented pairwise cross-modal mappings BibRef

Tang, J.J.[Jia-Jia], Liu, D.J.[Dong-Jun], Jin, X.Y.[Xuan-Yu], Peng, Y.[Yong], Zhao, Q.B.[Qi-Bin], Ding, Y.[Yu], Kong, W.Z.[Wan-Zeng],
BAFN: Bi-Direction Attention Based Fusion Network for Multimodal Sentiment Analysis,
CirSysVideo(33), No. 4, April 2023, pp. 1966-1978.
IEEE DOI 2304
Bidirectional control, Sentiment analysis, Termination of employment, Task analysis, Routing, Redundancy, attention mechanism BibRef

Dudzik, B.[Bernd], Hung, H.[Hayley], Neerincx, M.[Mark], Broekens, J.[Joost],
Collecting Mementos: A Multimodal Dataset for Context-Sensitive Modeling of Affect and Memory Processing in Responses to Videos,
AffCom(14), No. 2, April 2023, pp. 1249-1266.
IEEE DOI 2306
Videos, Media, Computational modeling, Films, Particle measurements, Mood, Atmospheric measurements, Multimodal dataset, personalization BibRef

Das, R.K.[Ring-Ki], Singh, T.D.[Thoudam Doren],
Multimodal Sentiment Analysis: A Survey of Methods, Trends, and Challenges,
Surveys(55), No. 13s, July 2023, pp. xx-yy.
DOI Link 2309
Survey, Sentiment. audio sentiment analysis, image sentiment analysis, text sentiment analysis, Multimodal sentiment analysis, transfer learning BibRef

Zhu, T.[Tong], Li, L.[Leida], Yang, J.F.[Ju-Feng], Zhao, S.C.[Si-Cheng], Liu, H.T.[Han-Tao], Qian, J.S.[Jian-Sheng],
Multimodal Sentiment Analysis With Image-Text Interaction Network,
MultMed(25), 2023, pp. 3375-3385.
IEEE DOI 2309
BibRef

Yu, J.F.[Jian-Fei], Chen, K.[Kai], Xia, R.[Rui],
Hierarchical Interactive Multimodal Transformer for Aspect-Based Multimodal Sentiment Analysis,
AffCom(14), No. 3, July 2023, pp. 1966-1978.
IEEE DOI 2310
BibRef

Mai, S.[Sijie], Zeng, Y.[Ying], Zheng, S.J.[Shuang-Jia], Hu, H.F.[Hai-Feng],
Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysis,
AffCom(14), No. 3, July 2023, pp. 2276-2289.
IEEE DOI 2310
BibRef

Lin, R.H.[Rong-Hao], Hu, H.F.[Hai-Feng],
Dynamically Shifting Multimodal Representations via Hybrid-Modal Attention for Multimodal Sentiment Analysis,
MultMed(26), 2024, pp. 2740-2755.
IEEE DOI 2402
Transformers, Acoustics, Visualization, Feature extraction, Task analysis, Logic gates, Sentiment analysis, hybrid-modal attention BibRef

Katada, S.[Shun], Okada, S.[Shogo], Komatani, K.[Kazunori],
Effects of Physiological Signals in Different Types of Multimodal Sentiment Estimation,
AffCom(14), No. 3, July 2023, pp. 2443-2457.
IEEE DOI 2310
BibRef

Zeng, J.D.[Jian-Dian], Zhou, J.T.[Jian-Tao], Liu, T.Y.[Tian-Yi],
Robust Multimodal Sentiment Analysis via Tag Encoding of Uncertain Missing Modalities,
MultMed(25), 2023, pp. 6301-6314.
IEEE DOI 2311
BibRef

Wang, D.[Di], Liu, S.[Shuai], Wang, Q.[Quan], Tian, Y.M.[Yu-Min], He, L.[Lihuo], Gao, X.B.[Xin-Bo],
Cross-Modal Enhancement Network for Multimodal Sentiment Analysis,
MultMed(25), 2023, pp. 4909-4921.
IEEE DOI 2311
BibRef

Ye, M.[Mang], Shi, Q.H.Y.[Qing-Hong-Ya], Su, K.[Kehua], Du, B.[Bo],
Cross-Modality Pyramid Alignment for Visual Intention Understanding,
IP(32), 2023, pp. 2190-2201.
IEEE DOI 2305
Exploring the potential and underlying meaning expressed in images. Visualization, Task analysis, Semantics, Feature extraction, Training, Image segmentation, Image color analysis, hierarchical relation BibRef

Liu, H.[Huan], Li, K.[Ke], Fan, J.P.[Jian-Ping], Yan, C.X.[Cai-Xia], Qin, T.[Tao], Zheng, Q.H.[Qing-Hua],
Social Image-Text Sentiment Classification With Cross-Modal Consistency and Knowledge Distillation,
AffCom(14), No. 4, October 2023, pp. 3332-3344.
IEEE DOI 2312
BibRef

Li, M.C.[Ming-Cheng], Yang, D.K.[Ding-Kang], Zhang, L.H.[Li-Hua],
Towards Robust Multimodal Sentiment Analysis Under Uncertain Signal Missing,
SPLetters(30), 2023, pp. 1497-1501.
IEEE DOI 2311
BibRef

Zhao, X.B.[Xian-Bing], Chen, Y.X.[Yin-Xin], Liu, S.[Sicen], Tang, B.[Buzhou],
Shared-Private Memory Networks For Multimodal Sentiment Analysis,
AffCom(14), No. 4, October 2023, pp. 2889-2900.
IEEE DOI Code:
WWW Link. 2312
BibRef

Cheng, H.J.[Hong-Ju], Yang, Z.Z.[Zi-Zhen], Zhang, X.Q.[Xiao-Qi], Yang, Y.[Yang],
Multimodal Sentiment Analysis Based on Attentional Temporal Convolutional Network and Multi-Layer Feature Fusion,
AffCom(14), No. 4, October 2023, pp. 3149-3163.
IEEE DOI 2312
BibRef

He, L.J.[Li-Jun], Wang, Z.Q.[Zi-Qing], Wang, L.[Liejun], Li, F.[Fan],
Multimodal Mutual Attention-Based Sentiment Analysis Framework Adapted to Complicated Contexts,
CirSysVideo(33), No. 12, December 2023, pp. 7131-7143.
IEEE DOI Code:
WWW Link. 2312
BibRef

Yuan, Z.Q.[Zi-Qi], Liu, Y.[Yihe], Xu, H.[Hua], Gao, K.[Kai],
Noise Imitation Based Adversarial Training for Robust Multimodal Sentiment Analysis,
MultMed(26), 2024, pp. 529-539.
IEEE DOI 2402
Training, Noise measurement, Visualization, Sentiment analysis, Robustness, Feature extraction, Data models, semantic reconstruction BibRef

Wang, D.[Di], Tian, C.[Changning], Liang, X.[Xiao], Zhao, L.[Lin], He, L.[Lihuo], Wang, Q.[Quan],
Dual-Perspective Fusion Network for Aspect-Based Multimodal Sentiment Analysis,
MultMed(26), 2024, pp. 4028-4038.
IEEE DOI 2402
Sentiment analysis, Task analysis, Data mining, Semantics, Syntactics, Feature extraction, Visualization, graph neural network BibRef

Qian, F.[Fan], Han, J.Q.[Ji-Qing], Guan, Y.D.[Ya-Dong], Song, W.J.[Wen-Jie], He, Y.J.[Yong-Jun],
Capturing High-Level Semantic Correlations via Graph for Multimodal Sentiment Analysis,
SPLetters(31), 2024, pp. 561-565.
IEEE DOI 2402
Semantics, Routing, Correlation, Feature extraction, Visualization, Self-supervised learning, Videos, Multimodal sentiment analysis, high-level semantic correlations BibRef

Sun, L.[Licai], Lian, Z.[Zheng], Liu, B.[Bin], Tao, J.H.[Jian-Hua],
Efficient Multimodal Transformer With Dual-Level Feature Restoration for Robust Multimodal Sentiment Analysis,
AffCom(15), No. 1, January 2024, pp. 309-325.
IEEE DOI 2403
Transformers, Robustness, Semantics, Data models, Computational modeling, Videos, Training, robustness BibRef

Huan, R.H.[Ruo-Hong], Zhong, G.W.[Guo-Wei], Chen, P.[Peng], Liang, R.H.[Rong-Hua],
UniMF: A Unified Multimodal Framework for Multimodal Sentiment Analysis in Missing Modalities and Unaligned Multimodal Sequences,
MultMed(26), 2024, pp. 5753-5768.
IEEE DOI 2404
Transformers, Sentiment analysis, Fuses, Training, Task analysis, Transformer cores, Semantics, Attention mechanism, unaligned multimodal sequences BibRef

Song, L.Y.[Ling-Yun], Chen, S.[Siyu], Meng, Z.Y.[Zi-Yang], Sun, M.X.[Ming-Xuan], Shang, X.[Xuequn],
FMSA-SC: A Fine-Grained Multimodal Sentiment Analysis Dataset Based on Stock Comment Videos,
MultMed(26), 2024, pp. 7294-7306.
IEEE DOI 2405
Videos, Stock markets, Annotations, Task analysis, Acoustics, Visualization, Web sites, Multimedia databases, neural networks, video signal processing BibRef

Yuan, Z.Q.[Zi-Qi], Zhang, B.Z.[Bao-Zheng], Xu, H.[Hua], Gao, K.[Kai],
Meta Noise Adaption Framework for Multimodal Sentiment Analysis With Feature Noise,
MultMed(26), 2024, pp. 7265-7277.
IEEE DOI 2405
Noise measurement, Task analysis, Training, Metalearning, Sentiment analysis, Adaptation models, Visualization, robust multimodal sentiment analysis BibRef

Singh, U.[Upendra], Abhishek, K.[Kumar], Azad, H.K.[Hiteshwar Kumar],
A Survey of Cutting-edge Multimodal Sentiment Analysis,
Surveys(56), No. 9, April 2024, pp. 227.
DOI Link 2405
Survey, Sentinment. Multimodal sentiment analysis, sentiment classifier, machine learning, emotion detection, modelling techniques BibRef

Lin, R.H.[Rong-Hao], Hu, H.F.[Hai-Feng],
Multi-Task Momentum Distillation for Multimodal Sentiment Analysis,
AffCom(15), No. 2, April 2024, pp. 549-565.
IEEE DOI 2406
Task analysis, Multitasking, Knowledge engineering, Sentiment analysis, Feature extraction, Visualization, Acoustics, multimodal sentiment analysis BibRef

Ji, X.Y.[Xiao-Yue], Dong, Z.[Zhekang], Zhou, G.[Guangdong], Lai, C.S.[Chun Sing], Qi, D.L.[Dong-Lian],
MLG-NCS: Multimodal Local-Global Neuromorphic Computing System for Affective Video Content Analysis,
SMCS(54), No. 8, August 2024, pp. 5137-5149.
IEEE DOI 2408
Memristors, Iron, Electrodes, Training, Sputtering, Neuromorphic engineering, Low latency communication, neuromorphic computing system (NCS) BibRef

Huang, J.[Jian], Ji, Y.L.[Yan-Li], Qin, Z.[Zhen], Yang, Y.[Yang], Shen, H.T.[Heng Tao],
Dominant SIngle-Modal SUpplementary Fusion (SIMSUF) for Multimodal Sentiment Analysis,
MultMed(26), 2024, pp. 8383-8394.
IEEE DOI 2408
Transformers, Sentiment analysis, Semantics, Task analysis, Fuses, Feature extraction, Representation learning, Multimodal fusion, transformer BibRef

Xie, Z.Y.[Zhu-Yang], Yang, Y.[Yan], Wang, J.[Jie], Liu, X.R.[Xiao-Rong], Li, X.F.[Xiao-Fan],
Trustworthy Multimodal Fusion for Sentiment Analysis in Ordinal Sentiment Space,
CirSysVideo(34), No. 8, August 2024, pp. 7657-7670.
IEEE DOI 2408
Uncertainty, Sentiment analysis, Estimation, Feature extraction, Reliability, Task analysis, Data models, ordinal regression BibRef

Li, M.[Meng], Zhu, Z.F.[Zhen-Fang], Li, K.[Kefeng], Zhou, L.H.[Li-Hua], Zhao, Z.[Zhen], Pei, H.L.[Hong-Li],
Joint training strategy of unimodal and multimodal for multimodal sentiment analysis,
IVC(149), 2024, pp. 105172.
Elsevier DOI 2408
Multimodal sentiment analysis, Multimodal fusion, Multimodal interaction BibRef

Zijun, W.[Wang], Naicheng, J.[Jiang], Xinyue, C.[Chao], Bin, S.[Sun],
Multi-task disagreement-reducing multimodal sentiment fusion network,
IVC(149), 2024, pp. 105158.
Elsevier DOI 2408
Multimodal sentiment analysis, Multimodal fusion, Sentiment disagreement, Multi-task learning BibRef

Liu, Z.J.[Zi-Jun], Cai, L.[Li], Yang, W.J.[Wen-Jie], Liu, J.H.[Jun-Hui],
Sentiment analysis based on text information enhancement and multimodal feature fusion,
PR(156), 2024, pp. 110847.
Elsevier DOI 2408
Sentiment analysis, Text information enhancement, Multimodal data fusion, Cross-modal attention mechanism, Sentiment lexicons BibRef

Wang, Q.L.[Qian-Long], Xu, H.L.[Hong-Ling], Wen, Z.Y.[Zhi-Yuan], Liang, B.[Bin], Yang, M.[Min], Qin, B.[Bing], Xu, R.F.[Rui-Feng],
Image-to-Text Conversion and Aspect-Oriented Filtration for Multimodal Aspect-Based Sentiment Analysis,
AffCom(15), No. 3, July 2024, pp. 1264-1278.
IEEE DOI 2409
Sentiment analysis, Visualization, Task analysis, Social networking (online), Filtration, Analytical models, pre-trained language model BibRef

Sharma, S.[Shivam], Ramaneswaran, S., Akhtar, M.S.[Md. Shad], Chakraborty, T.[Tanmoy],
Emotion-Aware Multimodal Fusion for Meme Emotion Detection,
AffCom(15), No. 3, July 2024, pp. 1800-1811.
IEEE DOI 2409
Task analysis, Emotion recognition, Social networking (online), Visualization, Mood, Affective computing, Internet, Emotion analysis, social media BibRef

Zhang, B.Z.[Bao-Zheng], Yuan, Z.Q.[Zi-Qi], Xu, H.[Hua], Gao, K.[Kai],
Crossmodal Translation Based Meta Weight Adaption for Robust Image-Text Sentiment Analysis,
MultMed(26), 2024, pp. 9949-9961.
IEEE DOI 2410
Robustness, Task analysis, Sentiment analysis, Semantics, Metalearning, Representation learning, robustness and reliability BibRef

Xie, S.F.[Shu-Fan], Chen, Q.H.[Qiao-Hong], Fang, X.[Xian], Sun, Q.[Qi],
Global information regulation network for multimodal sentiment analysis,
IVC(151), 2024, pp. 105297.
Elsevier DOI 2411
Multimodal sentiment analysis, Gate mechanism, Unsupervised learning, Contrastive learning BibRef

Liu, W.C.[Wu-Chao], Li, W.G.[Wen-Gen], Ruan, Y.P.[Yu-Ping], Shu, Y.[Yulou], Chen, J.T.[Jun-Tao], Li, Y.[Yina], Yu, C.[Caili], Zhang, Y.C.[Yi-Chao], Guan, J.H.[Ji-Hong], Zhou, S.[Shuigeng],
Weakly Correlated Multimodal Sentiment Analysis: New Dataset and Topic-Oriented Model,
AffCom(15), No. 4, October 2024, pp. 2070-2082.
IEEE DOI 2412
Sentiment analysis, Social networking (online), Reviews, Analytical models, Correlation, Visualization, Blogs, weak correlation BibRef

Zhang, T.[Ting], Song, B.[Bin], Zhang, Z.Y.[Zhi-Yong], Zhang, Y.J.[Ya-Juan],
Multimodal sentiment analysis based on multi-stage graph fusion networks under random missing modality conditions,
IET-IPR(19), No. 1, 2025, pp. e13310.
DOI Link 2501
missing modality, multimodal fusion, multimodal sentiment analysis, transformer BibRef

Zou, W.[Wang], Sun, X.[Xia], Lu, Q.[Qiang], Wang, X.[Xuxin], Feng, J.[Jun],
A vision and language hierarchical alignment for multimodal aspect-based sentiment analysis,
PR(162), 2025, pp. 111369.
Elsevier DOI 2503
Multimodal aspect-based sentiment analysis, Visual scene graph, Text dependency graph, Dynamic alignment matrix BibRef

Fan, C.[Cunhang], Zhu, K.[Kang], Tao, J.H.[Jian-Hua], Yi, G.F.[Guo-Feng], Xue, J.[Jun], Lv, Z.[Zhao],
Multi-Level Contrastive Learning: Hierarchical Alleviation of Heterogeneity in Multimodal Sentiment Analysis,
AffCom(16), No. 1, January 2025, pp. 207-222.
IEEE DOI 2503
Feature extraction, Contrastive learning, Semantics, Vectors, Convolution, TV, Sentiment analysis, Multimodal sentiment analysis, heterogeneity BibRef

Li, M.[Meng], Zhu, Z.F.[Zhen-Fang], Li, K.[Kefeng], Pei, H.L.[Hong-Li],
Diversity and Balance: Multimodal Sentiment Analysis Using Multimodal-Prefixed and Cross-Modal Attention,
AffCom(16), No. 1, January 2025, pp. 250-263.
IEEE DOI 2503
Data models, Sentiment analysis, Visualization, Task analysis, Analytical models, Acoustics, Transformers, cross-modal attention BibRef

Wang, Q.L.[Qian-Long], Wen, Z.Y.[Zhi-Yuan], Ding, K.Y.[Ke-Yang], Liang, B.[Bin], Xu, R.F.[Rui-Feng],
Cross-Domain Sentiment Analysis via Disentangled Representation and Prototypical Learning,
AffCom(16), No. 1, January 2025, pp. 264-276.
IEEE DOI 2503
Sentiment analysis, Reviews, Training, Task analysis, Feature extraction, Affective computing, Semantics, prototypical learning BibRef


Luo, W.[Wei], Xu, M.[Mengying], Lai, H.J.[Han-Jiang],
Multimodal Reconstruct and Align Net for Missing Modality Problem in Sentiment Analysis,
MMMod23(II: 411-422).
Springer DOI 2304
BibRef

Zhang, Q.G.[Qion-Gan], Shi, L.[Lei], Liu, P.[Peiyu], Zhu, Z.F.[Zhen-Fang], Xu, L.C.[Lian-Cheng],
IMCN: Identifying Modal Contribution Network for Multimodal Sentiment Analysis,
ICPR22(4729-4735)
IEEE DOI 2212
Sentiment analysis, Visualization, Analytical models, Noise reduction, Benchmark testing, Acoustics, modality contribution BibRef

Zhong, Q.[Qi], Wang, Q.[Qian], Liu, J.[Ji],
Combining Knowledge and Multi-modal Fusion for Meme Classification,
MMMod22(I:599-611).
Springer DOI 2203
Sentinment and offensive. BibRef

Wang, B.Q.[Bin-Qiang], Dong, G.[Gang], Zhao, Y.Q.[Ya-Qian], Li, R.G.[Ren-Gang], Cao, Q.C.[Qi-Chun], Chao, Y.Y.[Yin-Yin],
Non-Uniform Attention Network for Multi-modal Sentiment Analysis,
MMMod22(I:612-623).
Springer DOI 2203
BibRef

Patro, B.N.[Badri N.], Lunayach, M.[Mayank], Srivastava, D.[Deepankar], Sarvesh, S.[Sarvesh], Singh, H.[Hunar], Namboodiri, V.P.[Vinay P.],
Multimodal Humor Dataset: Predicting Laughter tracks for Sitcoms,
WACV21(576-585)
IEEE DOI
WWW Link. 2106
Dataset, Humor. Annotations, Semantics, Bit error rate, Manuals, Task analysis BibRef

Tashu, T.M.[Tsegaye Misikir], Horváth, T.[Tomáš],
Attention-based Multi-Modal Emotion Recognition from Art,
FAPER20(604-612).
Springer DOI 2103
BibRef

Garcia, N.[Noa], Vogiatzis, G.[George],
How to Read Paintings: Semantic Art Understanding with Multi-modal Retrieval,
CVAA18(II:676-691).
Springer DOI 1905
BibRef

Ullah, M.A., Islam, M.M., Azman, N.B., Zaki, Z.M.,
An overview of Multimodal Sentiment Analysis research: Opportunities and Difficulties,
IVPR17(1-6)
IEEE DOI 1704
Face BibRef

Nemati, S., Naghsh-Nilchi, A.R.,
Exploiting evidential theory in the fusion of textual, audio, and visual modalities for affective music video retrieval,
IPRIA17(222-228)
IEEE DOI 1712
emotion recognition, image fusion, inference mechanisms, sentiment analysis, social networking (online), Lexicon-based sentiment analysis BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Rendering Specific Surfaces, Applied Rendering .


Last update:Mar 12, 2025 at 14:27:03