11.2.1.3.20 Visual Sentiment Evaluation

Memotion Dataset 7k,
2019.
WWW Link. Dataset, Sentinment. Memotion Dataset. Dataset for sentiment classification of memes.

Neviarouskaya, A., Prendinger, H., Ishizuka, M.,
SentiFul: A Lexicon for Sentiment Analysis,
AffCom(2), No. 1, 2011, pp. 22-36.
IEEE DOI 1202
BibRef

Clavel, C., Callejas, Z.,
Sentiment Analysis: From Opinion Mining to Human-Agent Interaction,
AffCom(7), No. 1, January 2016, pp. 74-93.
IEEE DOI 1603
Analytical models BibRef

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

Choi, Y., Wiebe, J., Mihalcea, R.,
Coarse-Grained +/-Effect Word Sense Disambiguation for Implicit Sentiment Analysis,
AffCom(8), No. 4, October 2017, pp. 471-479.
IEEE DOI 1712
Bridges, Gold, Knowledge based systems, Medical services, Sentiment analysis, Standards, Training data, Sentiment analysis, word sense disambiguation BibRef

Dragoni, M., Petrucci, G.,
A Neural Word Embeddings Approach for Multi-Domain Sentiment Analysis,
AffCom(8), No. 4, October 2017, pp. 457-470.
IEEE DOI 1712
Analytical models, Buildings, Context, Machine learning, Sentiment analysis, Social network services, neural networks 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

Campos, V.[Víctor], Jou, B.[Brendan], Giró-i-Nieto, X.[Xavier],
From pixels to sentiment: Fine-tuning CNNs for visual sentiment prediction,
IVC(65), No. 1, 2017, pp. 15-22.
Elsevier DOI 1709
Sentiment BibRef

Sharma, S.[Srishti], Chakraverty, S.[Shampa], Sharma, A.[Akhil], Kaur, J.[Jasleen],
A context-based algorithm for sentiment analysis,
IJCVR(7), No. 5, 2017, pp. 558-573.
DOI Link 1709
BibRef

Weichselbraun, A., Gindl, S., Fischer, F., Vakulenko, S., Scharl, A.,
Aspect-Based Extraction and Analysis of Affective Knowledge from Social Media Streams,
IEEE_Int_Sys(32), No. 3, May 2017, pp. 80-88.
IEEE DOI 1706
Automobiles, Companies, Data mining, Knowledge acquisition, Media, Sentiment analysis, Social network services, affective knowledge extraction, artificial intelligence, aspect-based sentiment analysis, linked data, opinion targets, social, media BibRef

Pappas, N.[Nikolaos], Redi, M.[Miriam], Topkara, M.[Mercan], Liu, H.Y.[Hong-Yi], Jou, B.[Brendan], Chen, T.[Tao], Chang, S.F.[Shih-Fu],
Multilingual visual sentiment concept clustering and analysis,
MultInfoRetr(6), No. 1, March 2017, pp. 51-70.
Springer DOI 1704
BibRef

Dragoni, M., Poria, S., Cambria, E.,
OntoSenticNet: A Commonsense Ontology for Sentiment Analysis,
IEEE_Int_Sys(33), No. 3, May 2018, pp. 77-85.
IEEE DOI 1808
Ontologies, Sentiment analysis, Semantics, Task analysis, Affective computing, Feature extraction, sentiment analysis, artificial intelligence BibRef

Liu, A.[Anan], Shi, Y.D.[Ying-Di], Jing, P.G.[Pei-Guang], Liu, J.[Jing], Su, Y.T.[Yu-Ting],
Low-rank regularized multi-view inverse-covariance estimation for visual sentiment distribution prediction,
JVCIR(57), 2018, pp. 243-252.
Elsevier DOI 1812
Using images to express opinions and share experiences. Image sentiment, Label distribution learning, Structured sparsity, Low-rank BibRef

Yang, J., She, D., Sun, M., Cheng, M., Rosin, P.L., Wang, L.,
Visual Sentiment Prediction Based on Automatic Discovery of Affective Regions,
MultMed(20), No. 9, September 2018, pp. 2513-2525.
IEEE DOI 1809
image representation, learning (artificial intelligence), neural nets, object tracking, automatic discovery, visual sentiment analysis BibRef

Ding, X., Chen, Z.,
Improving Saliency Detection Based on Modeling Photographer's Intention,
MultMed(21), No. 1, January 2019, pp. 124-134.
IEEE DOI 1901
Saliency detection, Visualization, Psychology, Image color analysis, Task analysis, Feature extraction, intention rate BibRef

Liu, X.[Xuan], Li, N.[Na], Xia, Y.[Yong],
Affective image classification by jointly using interpretable art features and semantic annotations,
JVCIR(58), 2019, pp. 576-588.
Elsevier DOI 1901
Affective image classification, Discrete emotion space, Deep convolutional neural network (DCNN), Feature extraction, Support vector machine (SVM) BibRef

Jin, X.[Xin], Wu, L.[Le], Li, X.D.[Xiao-Dong], Zhang, X.K.[Xiao-Kun], Chi, J.Y.[Jing-Ying], Peng, S.W.[Si-Wei], Ge, S.M.[Shi-Ming], Zhao, G.[Geng], Li, S.Y.[Shu-Ying],
ILGNet: inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation,
IET-CV(13), No. 2, March 2019, pp. 206-212.
DOI Link 1902
BibRef

Pluta, M.[Magda], Mitka, B.[Bartosz],
V-Factor Indicator in the Assessment of the Change in the Attractiveness of View as a Result of the Implementation of a Specific Planning Scenario,
IJGI(8), No. 2, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Zhang, X., Li, Z., Constable, M., Chan, K.L., Tang, Z., Tang, G.,
Pose-Based Composition Improvement for Portrait Photographs,
CirSysVideo(29), No. 3, March 2019, pp. 653-668.
IEEE DOI 1903
Painting, Face, Pose estimation, Training, Databases, Area measurement, Composition improvement, pose, portrait BibRef

Cui, C.R.[Chao-Ran], Liu, H.H.[Hui-Hui], Lian, T.[Tao], Nie, L.Q.[Li-Qiang], Zhu, L.[Lei], Yin, Y.L.[Yi-Long],
Distribution-Oriented Aesthetics Assessment With Semantic-Aware Hybrid Network,
MultMed(21), No. 5, May 2019, pp. 1209-1220.
IEEE DOI 1905
convolutional neural nets, image representation, object recognition, image aesthetics assessment, semantic fusion BibRef

Wang, M.[Meili], Guo, S.H.[Shi-Hui], Liao, M.H.[Ming-Hong], He, D.J.[Dong-Jian], Chang, J.[Jian], Zhang, J.J.[Jian-Jun],
Action snapshot with single pose and viewpoint,
VC(35), No. 4, April 2019, pp. 507-520.
Springer DOI 1906
Select a meaningful representative moment from an action performance. BibRef

Zhang, W.J.[Wen-Jie], Yao, Y.Y.[Yi-Yang], Wang, J.X.[Jin-Xiong], Xiang, X.Y.[Xin-Yu], Shu, P.[Peng],
RETRACTED: Image quality tendency modeling by fusing multiple visual cues,
JVCIR(69), 2020, pp. 102841.
Elsevier DOI 2006
BibRef
And: Original: JVCIR(62), 2019, pp. 117-128. 1908
Machine learning, Multi-cue fusion, Aesthetic tendency, Flickr, Graph mining BibRef

Zeng, H., Cao, Z., Zhang, L., Bovik, A.C.,
A Unified Probabilistic Formulation of Image Aesthetic Assessment,
IP(29), No. , 2020, pp. 1548-1561.
IEEE DOI 1911
Task analysis, Probabilistic logic, Computational modeling, Measurement, Predictive models, Training, Explosives, unified probabilistic formulation 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

Li, M.[Mao], Lv, J.C.[Jian-Cheng], Tang, C.W.[Chen-Wei],
Aesthetic assessment of paintings based on visual balance,
IET-IPR(13), No. 14, 12 December 2019, pp. 2821-2828.
DOI Link 1912
BibRef

Wang, W.S.[Wen-Shan], Yang, S.[Su], Zhang, W.S.[Wei-Shan], Zhang, J.L.[Jiu-Long],
Neural aesthetic image reviewer,
IET-CV(13), No. 8, December 2019, pp. 749-758.
DOI Link 1912
BibRef

Cetinic, E.[Eva], Lipic, T.[Tomislav], Grgic, S.[Sonja],
Learning the Principles of Art History with convolutional neural networks,
PRL(129), 2020, pp. 56-62.
Elsevier DOI 2001
Convolutional neural networks, Fine art, High-level image features, Wölfflin BibRef

Li, L., Zhu, H., Zhao, S., Ding, G., Lin, W.,
Personality-Assisted Multi-Task Learning for Generic and Personalized Image Aesthetics Assessment,
IP(29), 2020, pp. 3898-3910.
IEEE DOI 2002
Image aesthetics assessment, generic and personalized image aesthetics, personality traits, Siamese network BibRef

She, D., Yang, J., Cheng, M., Lai, Y., Rosin, P.L., Wang, L.,
WSCNet: Weakly Supervised Coupled Networks for Visual Sentiment Classification and Detection,
MultMed(22), No. 5, May 2020, pp. 1358-1371.
IEEE DOI 2005
Visualization, Proposals, Task analysis, Feature extraction, Sentiment analysis, Training, Convolutional neural networks, convolutional neural networks BibRef

Yang, J., She, D., Lai, Y., Rosin, P.L., Yang, M.,
Weakly Supervised Coupled Networks for Visual Sentiment Analysis,
CVPR18(7584-7592)
IEEE DOI 1812
Visualization, Proposals, Feature extraction, Sentiment analysis, Task analysis, Training, Twitter BibRef

Ortis, A.[Alessandro], Farinella, G.M.[Giovanni Maria], Battiato, S.[Sebastiano],
Survey on visual sentiment analysis,
IET-IPR(14), No. 8, 19 June 2020, pp. 1440-1456.
DOI Link 2005
BibRef
And:
Prediction of Social Image Popularity Dynamics,
CIAP19(II:572-582).
Springer DOI 1909
BibRef

Reddy, G.V.[Gajjala Viswanatha], Mukherjee, S.[Snehasis], Thakur, M.[Mainak],
Measuring photography aesthetics with deep CNNs,
IET-IPR(14), No. 8, 19 June 2020, pp. 1561-1570.
DOI Link 2005
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

Kim, W., Choi, J., Lee, J.,
Objectivity and Subjectivity in Aesthetic Quality Assessment of Digital Photographs,
AffCom(11), No. 3, July 2020, pp. 493-506.
IEEE DOI 2008
Quality assessment, Photography, Databases, Visualization, Semantics, Computational modeling, Image processing, Photograph, subjectivity, user comment analysis BibRef

Zhao, L.[Lin], Shang, M.M.[Mei-Mei], Gao, F.[Fei], Li, R.S.[Rong-Sheng], Huang, F.[Fei], Yu, J.[Jun],
Representation learning of image composition for aesthetic prediction,
CVIU(199), 2020, pp. 103024.
Elsevier DOI 2009
Photo quality assessment, Image quality assessment, Deep learning, Aesthetic, Representation learning BibRef

Zhang, C.[Chao], Liu, S.[Sitong], Li, H.[Huizi],
Quality-guided video aesthetics assessment with social media context,
JVCIR(71), 2020, pp. 102643.
Elsevier DOI 2009
Video aesthetic assessment, Structure correlation, SVM 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

Liu, J., Lv, J., Yuan, M., Zhang, J., Su, Y.,
ABSNet: Aesthetics-Based Saliency Network Using Multi-Task Convolutional Network,
SPLetters(27), 2020, pp. 2014-2018.
IEEE DOI 2012
Visualization, Task analysis, Feature extraction, Saliency detection, Signal processing algorithms, visual saliency detection BibRef

Li, K.[Ke], Wu, Y.X.[Yu-Xia], Xue, Y.[Yao], Qian, X.M.[Xue-Ming],
Viewpoint Recommendation Based on Object-Oriented 3D Scene Reconstruction,
MultMed(23), 2021, pp. 257-267.
IEEE DOI 2012
Viewpoints for taking aesthetic photographs of a place-of-interest (POI). Object detection, Cameras, Feature extraction, Image reconstruction, Social networking (online), viewpoint recommendation BibRef

Ragusa, E.[Edoardo], Gianoglio, C.[Christian], Zunino, R.[Rodolfo], Gastaldo, P.[Paolo],
Image Polarity Detection on Resource-Constrained Devices,
IEEE_Int_Sys(35), No. 6, November 2020, pp. 50-57.
IEEE DOI 2012
Emotional content in the image. Feature extraction, Intelligent systems, Detectors, Object recognition, Computational modeling, Twitter BibRef

Lotfian, M.[Maryam], Ingensand, J.[Jens], Brovelli, M.A.[Maria Antonia],
A Framework for Classifying Participant Motivation that Considers the Typology of Citizen Science Projects,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link 2012
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

Yao, X.X.[Xing-Xu], She, D.Y.[Dong-Yu], Zhang, H.W.[Hai-Wei], Yang, J.F.[Ju-Feng], Cheng, M.M.[Ming-Ming], Wang, L.[Liang],
Adaptive Deep Metric Learning for Affective Image Retrieval and Classification,
MultMed(23), 2021, pp. 1640-1653.
IEEE DOI 2106
Measurement, Visualization, Semantics, Feature extraction, Task analysis, Image analysis, Image retrieval, visual sentiment analysis BibRef

Miyata, M.[Mari], Aizawa, K.[Kiyoharu],
Estimation of Semantic Impressions from Portraits,
IEICE(E104-D), No. 6, June 2021, pp. 863-872.
WWW Link. 2106
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

Lin, F.Q.[Fu-Qiang], Song, Y.P.[Yi-Ping], Ma, X.K.[Xing-Kong], Min, E.[Erxue], Liu, B.[Bo],
Sentiment-Aware Emoji Insertion Via Sequence Tagging,
MultMedMag(28), No. 2, April 2021, pp. 40-48.
IEEE DOI 2107
Task analysis, Tagging, Social networking (online), Sentiment analysis, Blogs, Semantics 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

Pilarczyk, J.[Joanna], Janeczko, W.[Weronika], Sterna, R.[Radoslaw], Kuniecki, M.[Michal],
Are emotional objects visually salient? The Emotional Maps Database,
JVCIR(79), 2021, pp. 103221.
Elsevier DOI 2109
Meaning maps, Saliency, Emotion, Arousal, Natural scenes, Key objects BibRef

Yang, M.[Min], Yin, W.P.[Wen-Peng], Qu, Q.[Qiang], Tu, W.T.[Wen-Ting], Shen, Y.[Ying], Chen, X.J.[Xiao-Jun],
Neural Attentive Network for Cross-Domain Aspect-Level Sentiment Classification,
AffCom(12), No. 3, July 2021, pp. 761-775.
IEEE DOI 2109
Adaptation models, Neural networks, Task analysis, Computational modeling, Probabilistic logic, multi-view attention BibRef

Yamamoto, T.[Takahisa], Takeuchi, S.[Shiki], Nakazawa, A.[Atsushi],
Image Emotion Recognition Using Visual and Semantic Features Reflecting Emotional and Similar Objects,
IEICE(E104-D), No. 10, October 2021, pp. 1691-1701.
WWW Link. 2110
BibRef

Thomas, C.[Christopher], Kovashka, A.[Adriana],
Predicting Visual Political Bias Using Webly Supervised Data and an Auxiliary Task,
IJCV(129), No. 11, November 2021, pp. 2978-3003.
Springer DOI 2110
BibRef

Thomas, C.[Christopher], Kovashka, A.[Adriana],
Seeing Behind the Camera: Identifying the Authorship of a Photograph,
CVPR16(3494-3502)
IEEE DOI 1612
180,000 images from 41 well-known photographers. BibRef

Yang, J.Y.[Jing-Yuan], Gao, X.B.[Xin-Bo], Li, L.[Leida], Wang, X.M.[Xiu-Mei], Ding, J.S.[Jin-Shan],
SOLVER: Scene-Object Interrelated Visual Emotion Reasoning Network,
IP(30), 2021, pp. 8686-8701.
IEEE DOI 2110
Visualization, Feature extraction, Psychology, Task analysis, Deep learning, Convolutional neural networks, Semantics, attention mechanism BibRef

Wang, S.F.[Shang-Fei], Wang, C.[Can], Chen, T.F.[Tan-Fang], Wang, Y.[Yaxin], Shu, Y.Y.[Yang-Yang], Ji, Q.[Qiang],
Video Affective Content Analysis by Exploring Domain Knowledge,
AffCom(12), No. 4, October 2021, pp. 1002-1017.
IEEE DOI 2112
Lighting, Image color analysis, Visualization, Emotion recognition, Feature extraction, Grammar, Music, Content analysis, visual/speech/music elements BibRef

Qi, F.[Fan], Yang, X.S.[Xiao-Shan], Xu, C.S.[Chang-Sheng],
Emotion Knowledge Driven Video Highlight Detection,
MultMed(23), 2021, pp. 3999-4013.
IEEE DOI 2112
Visualization, Training data, Predictive models, Training, Semantics, Emotion recognition, Computational modeling, Deep ranking, video highlight detection BibRef

Long, Y.F.[Yun-Fei], Xiang, R.[Rong], Lu, Q.[Qin], Huang, C.R.[Chu-Ren], Li, M.L.[Ming-Lei],
Improving Attention Model Based on Cognition Grounded Data for Sentiment Analysis,
AffCom(12), No. 4, October 2021, pp. 900-912.
IEEE DOI 2112
Sentiment analysis, Analytical models, Cognition, Data models, Context modeling, Deep learning, Affective lexicons, attention model BibRef

Yao, X.X.[Xing-Xu], Zhao, S.C.[Si-Cheng], Lai, Y.K.[Yu-Kun], She, D.Y.[Dong-Yu], Liang, J.[Jie], Yang, J.F.[Ju-Feng],
APSE: Attention-Aware Polarity-Sensitive Embedding for Emotion-Based Image Retrieval,
MultMed(23), 2021, pp. 4469-4482.
IEEE DOI 2112
BibRef
Earlier: A1, A4, A2, A5, A3, A6:
Attention-Aware Polarity Sensitive Embedding for Affective Image Retrieval,
ICCV19(1140-1150)
IEEE DOI 2004
Visualization, Task analysis, Psychology, Image retrieval, Feature extraction, Image color analysis, Emotion recognition, visual sentiment analysis. affective computing, content-based retrieval, data mining, emotion recognition, image representation, Psychology BibRef

Bisogni, C.[Carmen], Cascone, L.[Lucia], Castiglione, A.[Aniello], Passero, I.[Ignazio],
Deep learning for emotion driven user experiences,
PRL(152), 2021, pp. 115-121.
Elsevier DOI 2112
Deep learning, User emotions, User experience 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

Wang, H.L.[Han-Li], Tang, P.J.[Peng-Jie], Li, Q.Y.[Qin-Yu], Cheng, M.[Meng],
Emotion Expression With Fact Transfer for Video Description,
MultMed(24), 2022, pp. 715-727.
IEEE DOI 2202
Visualization, Semantics, Sentiment analysis, Measurement, Training, Databases, Video description, Convolutional neural network, video description BibRef

Xiong, X.[Xi], Qiao, S.J.[Shao-Jie], Han, N.[Nan], Li, Y.Y.[Yuan-Yuan], Xiong, F.[Fei], He, L.[Ling],
Affective Impression: Sentiment-Awareness POI Suggestion via Embedding in Heterogeneous LBSNs,
AffCom(13), No. 1, January 2022, pp. 272-284.
IEEE DOI 2203
Heterogeneous networks, Information technology, Social networking (online), Probabilistic logic, Data integrity, probabilistic graphical model BibRef

de Paula, D.[Diandre], Alexandre, L.A.[Luís A.],
Facial Emotion Recognition for Sentiment Analysis of Social Media Data,
IbPRIA22(207-217).
Springer DOI 2205
BibRef

Benini, S.[Sergio], Savardi, M.[Mattia], Bálint, K.[Katalin], Kovács, A.B.[András Bálint], Signoroni, A.[Alberto],
On the Influence of Shot Scale on Film Mood and Narrative Engagement in Film Viewers,
AffCom(13), No. 2, April 2022, pp. 592-603.
IEEE DOI 2206
Mood, Motion pictures, Cameras, Convolutional neural networks, Emotional responses, Barium, Complexity theory, Shot scale, convolutional neural networks BibRef

Yang, T.[Tao], Yin, Q.[Qing], Yang, L.[Lei], Wu, O.[Ou],
Aspect-Based Sentiment Analysis with New Target Representation and Dependency Attention,
AffCom(13), No. 2, April 2022, pp. 640-650.
IEEE DOI 2206
Sentiment analysis, Syntactics, Encoding, Deep learning, Grammar, Recurrent neural networks, Learning systems, ABSA, dependency attention BibRef

Nazir, A.[Ambreen], Rao, Y.[Yuan], Wu, L.[Lianwei], Sun, L.[Ling],
Issues and Challenges of Aspect-based Sentiment Analysis: A Comprehensive Survey,
AffCom(13), No. 2, April 2022, pp. 845-863.
IEEE DOI 2206
Survey, Sentiment Analysis. Sentiment analysis, Social networking (online), Data mining, Machine learning, Task analysis, Tools, Sun, Aspect, social media BibRef

Salminen, M.[Mikko], Järvelä, S.[Simo], Ruonala, A.[Antti], Harjunen, V.J.[Ville J.], Hamari, J.H.[Ju-Ho], Jacucci, G.[Giulio], Ravaja, N.[Niklas],
Evoking Physiological Synchrony and Empathy Using Social VR With Biofeedback,
AffCom(13), No. 2, April 2022, pp. 746-755.
IEEE DOI 2206
Visualization, Biological control systems, Electroencephalography, Physiology, Synchronization, virtual reality BibRef

Shukla, A.[Abhinav], Gullapuram, S.S.[Shruti Shriya], Katti, H.[Harish], Kankanhalli, M.[Mohan], Winkler, S.[Stefan], Subramanian, R.[Ramanathan],
Recognition of Advertisement Emotions With Application to Computational Advertising,
AffCom(13), No. 2, April 2022, pp. 781-792.
IEEE DOI 2206
Streaming media, Advertising, Electroencephalography, Motion pictures, Brain modeling, Emotion recognition, Encoding, ad insertion BibRef

Mehbodniya, A.[Abolfazl], Rao, M.V.[M. Varaprasad], David, L.G.[Leo Gertrude], Nigel, K.G.J.[K. Gerard Joe], Vennam, P.[Preethi],
Online product sentiment analysis using random evolutionary whale optimization algorithm and deep belief network,
PRL(159), 2022, pp. 1-8.
Elsevier DOI 2206
BibRef

Xu, J.[Jie], Li, Z.[Zhoujun], Huang, F.[Feiran], Li, C.Z.[Chao-Zhuo], Yu, P.S.[Philip S.],
Visual Sentiment Analysis With Social Relations-Guided Multiattention Networks,
Cyber(52), No. 6, June 2022, pp. 4472-4484.
IEEE DOI 2207
Visualization, Feature extraction, Sentiment analysis, Correlation, Semantics, Heterogeneous networks, Analytical models, social image BibRef

Zhang, T.[Tong], Gong, X.R.[Xin-Rong], Chen, C.L.P.[C. L. Philip],
BMT-Net: Broad Multitask Transformer Network for Sentiment Analysis,
Cyber(52), No. 7, July 2022, pp. 6232-6243.
IEEE DOI 2207
Task analysis, Sentiment analysis, Feature extraction, Context modeling, Bit error rate, Analytical models, sentiment analysis BibRef

Li, C.H.[Chen-Hui], Zhang, P.Y.[Pei-Ying], Wang, C.B.[Chang-Bo],
Harmonious Textual Layout Generation Over Natural Images via Deep Aesthetics Learning,
MultMed(24), 2022, pp. 3416-3428.
IEEE DOI 2207
Layout, Visualization, Graphics, Saliency detection, Proposals, Feature extraction, Task analysis, Textual layout, deep learning BibRef

Nazir, A.[Ambreen], Rao, Y.[Yuan], Wu, L.[Lianwei], Sun, L.[Ling],
IAF-LG: An Interactive Attention Fusion Network With Local and Global Perspective for Aspect-Based Sentiment Analysis,
AffCom(13), No. 4, October 2022, pp. 1730-1742.
IEEE DOI 2212
Semantics, Task analysis, Neural networks, Sentiment analysis, Logic gates, Context modeling, Computer architecture, semantics BibRef

Thakkar, A.[Ankit], Mungra, D.[Dhara], Agrawal, A.[Anjali], Chaudhari, K.[Kinjal],
Improving the Performance of Sentiment Analysis Using Enhanced Preprocessing Technique and Artificial Neural Network,
AffCom(13), No. 4, October 2022, pp. 1771-1782.
IEEE DOI 2212
Social networking (online), Task analysis, Support vector machines, Motion pictures, Feature extraction, neurosent BibRef

Ren, H.P.[Hao-Peng], Cai, Y.[Yi], Zeng, Y.S.[Yu-Shi], Ye, J.H.[Jing-Hui], Leung, H.F.[Ho-Fung], Li, Q.[Qing],
Aspect-Opinion Correlation Aware and Knowledge-Expansion Few Shot Cross-Domain Sentiment Classification,
AffCom(13), No. 4, October 2022, pp. 1691-1704.
IEEE DOI 2212
Feature extraction, Task analysis, Semantics, Training, Knowledge engineering, Syntactics, Sentiment analysis, few-shot learning BibRef

Matsiiako, V.[Vladyslav], Frasincar, F.[Flavius], Boekestijn, D.[David],
Aspect-Based Sentiment Quantification,
AffCom(13), No. 4, October 2022, pp. 1718-1729.
IEEE DOI 2212
Task analysis, Training, Aggregates, Costs, Classification algorithms, Support vector machines, Sociology, sentiment quantification 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

Xu, Y.J.[Yu-Jun], Yao, E.[Enguang], Liu, C.Y.[Chao-Yue], Liu, Q.D.[Qi-Dong], Xu, M.L.[Ming-Liang], y
A novel ensemble model with two-stage learning for joint dialog act recognition and sentiment classification,
PRL(165), 2023, pp. 77-83.
Elsevier DOI 2301
Dialog act recognition, Sentiment classification, Two-stage learning, Joint model BibRef

Nasfi, R.[Rim], Bouguila, N.[Nizar],
Sentiment Analysis from User Reviews Using a Hybrid Generative-Discriminative HMM-SVM Approach,
SSSPR22(74-83).
Springer DOI 2301
BibRef

Abdullah, T.[Tariq], Ahmet, A.[Ahmed],
Deep Learning in Sentiment Analysis: Recent Architectures,
Surveys(55), No. 8, December 2022, pp. xx-yy.
DOI Link 2301
Survey, Sentiment Analysis. cross-domain sentiment analysis, transfer learning, cross-lingual sentiment analysis, sentiment analysis BibRef

Liu, A.A.[An-An], Du, H.W.[Hong-Wei], Xu, N.[Ning], Zhang, Q.[Quan], Zhang, S.Y.[Shen-Yuan], Tang, Y.J.[Ye-Jun], Li, X.Y.[Xuan-Ya],
Exploring visual relationship for social media popularity prediction,
JVCIR(90), 2023, pp. 103738.
Elsevier DOI 2301
Social media popularity prediction, Visual relationship, Content-based filtering, Interpretability BibRef

Park, E.H.[Eun Hee], Storey, V.C.[Veda C.],
Emotion Ontology Studies: A Framework for Expressing Feelings Digitally and Its Application to Sentiment Analysis,
Surveys(55), No. 9, January 2023, pp. xx-yy.
DOI Link 2302
Survey, Sentiment Analysis. sentiment analysis, dimensional emotion ontology, affect, discrete emotion ontology, Framework of Emotion Ontologies, emotion BibRef

Poria, S.[Soujanya], Hazarika, D.[Devamanyu], Majumder, N.[Navonil], Mihalcea, R.[Rada],
Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Research,
AffCom(14), No. 1, January 2023, pp. 108-132.
IEEE DOI 2303
Sentiment analysis, Task analysis, Syntactics, Cognition, Semantics, Context modeling, bias in sentiment analysis systems BibRef

Zhang, X.[Xing], Xu, J.Y.[Jing-Yun], Cai, Y.[Yi], Tan, X.W.[Xing-Wei], Zhu, C.X.[Chang-Xi],
Detecting Dependency-Related Sentiment Features for Aspect-Level Sentiment Classification,
AffCom(14), No. 1, January 2023, pp. 196-210.
IEEE DOI 2303
Feature extraction, Task analysis, Syntactics, Batteries, Sentiment analysis, Semantics, bidirectional long short-term memory BibRef

Liang, B.[Bin], Yin, R.[Rongdi], Du, J.C.[Jia-Chen], Gui, L.[Lin], He, Y.L.[Yu-Lan], Yang, M.[Min], Xu, R.F.[Rui-Feng],
Embedding Refinement Framework for Targeted Aspect-Based Sentiment Analysis,
AffCom(14), No. 1, January 2023, pp. 279-293.
IEEE DOI 2303
Sentiment analysis, Task analysis, Feature extraction, Context modeling, Data mining, Semantics, Computer science, affective knowledge 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

Su, Y.T.[Yu-Ting], Zhao, W.[Wei], Jing, P.G.[Pei-Guang], Nie, L.Q.[Li-Qiang],
Exploiting Low-Rank Latent Gaussian Graphical Model Estimation for Visual Sentiment Distributions,
MultMed(25), 2023, pp. 1243-1255.
IEEE DOI 2305
Correlation, Visualization, Graphical models, Covariance matrices, Multivariate regression, Estimation, Sentiment analysis, visual sentiment analysis 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

Zhang, H.M.[Hai-Min], Xu, M.[Min],
Multiscale Emotion Representation Learning for Affective Image Recognition,
MultMed(25), 2023, pp. 2203-2212.
IEEE DOI 2306
Feature extraction, Image recognition, Emotion recognition, Task analysis, Representation learning, Face recognition, multiscale representation learning 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

He, K.[Kai], Mao, R.[Rui], Gong, T.[Tieliang], Li, C.[Chen], Cambria, E.[Erik],
Meta-Based Self-Training and Re-Weighting for Aspect-Based Sentiment Analysis,
AffCom(14), No. 3, July 2023, pp. 1731-1742.
IEEE DOI 2310
BibRef

Lopes, C.R.[Cesar Rafael], Minetto, R.[Rodrigo], Delgado, M.R.[Myriam Regattieri], Silva, T.H.[Thiago H],
PerceptSent: Exploring Subjectivity in a Novel Dataset for Visual Sentiment Analysis,
AffCom(14), No. 3, July 2023, pp. 1817-1831.
IEEE DOI 2310
BibRef

Wang, K.[Ke], Wan, X.J.[Xiao-Jun],
Counterfactual Representation Augmentation for Cross-Domain Sentiment Analysis,
AffCom(14), No. 3, July 2023, pp. 1979-1990.
IEEE DOI 2310
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

Zhao, S.C.[Si-Cheng], Hong, X.P.[Xiao-Peng], Yang, J.F.[Ju-Feng], Zhao, Y.Y.[Yan-Yan], Ding, G.[Guiguang],
Toward Label-Efficient Emotion and Sentiment Analysis,
PIEEE(111), No. 10, October 2023, pp. 1159-1197.
IEEE DOI 2310
BibRef

Wang, J.Z.[James Z.], Zhao, S.C.[Si-Cheng], Wu, C.Y.[Chen-Yan], Adams, R.B.[Reginald B.], Newman, M.G.[Michelle G.], Shafir, T.[Tal], Tsachor, R.[Rachelle],
Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion,
PIEEE(111), No. 10, October 2023, pp. 1236-1286.
IEEE DOI 2310
BibRef

Quan, X.J.[Xiao-Jun], Min, Z.C.[Zheng-Cheng], Li, K.[Kun], Yang, Y.[Yunyi],
Compound Aspect Extraction by Augmentation and Constituency Lattice,
AffCom(14), No. 3, July 2023, pp. 2323-2335.
IEEE DOI 2310
BibRef

Lee, S.E.[Sang-Eun], Ryu, C.[Chaeeun], Park, E.[Eunil],
OSANet: Object Semantic Attention Network for Visual Sentiment Analysis,
MultMed(25), 2023, pp. 7139-7148.
IEEE DOI 2311
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

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

Ibrohim, M.O.[Muhammad Okky], Bosco, C.[Cristina], Basile, V.[Valerio],
Sentiment Analysis for the Natural Environment: A Systematic Review,
Surveys(56), No. 4, November 2023, pp. xx-yy.
DOI Link 2312
Survey, Sentiment. sentiment analysis, Natural environment, data-driven policy, natural language processing (NLP), systematic review 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

Cao, Y.K.[Yu-Kun], Tang, Y.J.[Yi-Jia], Du, H.Z.[Hai-Zhou], Xu, F.F.[Fei-Fei], Wei, Z.Y.[Zi-Yue], Jin, C.[Chengkun],
Heterogeneous Reinforcement Learning Network for Aspect-Based Sentiment Classification With External Knowledge,
AffCom(14), No. 4, October 2023, pp. 3362-3375.
IEEE DOI 2312
BibRef

Rathod, B.[Bhoomika], Vanzara, R.[Rakeshkumar], Pandya, D.[Devang],
A recent survey on perceived group sentiment analysis,
JVCIR(97), 2023, pp. 103988.
Elsevier DOI 2312
Group emotion recognition, Machine learning, Deep learning, Fusion methods, Sentiment analysis BibRef

Wang, X.H.[Xiao-Hua], Yang, J.[Jie], Hu, M.[Min], Ren, F.[Fuji],
EERCA-ViT: Enhanced Effective Region and Context-Aware Vision Transformers for image sentiment analysis,
JVCIR(97), 2023, pp. 103968.
Elsevier DOI 2312
Visual sentiment analysis, Enhanced Effective Region, Context-aware, Vision transformer, Double branch BibRef

Hu, M.T.[Meng-Ting], Zhao, S.[Shiwan], Guo, H.L.[Hong-Lei], Su, Z.[Zhong],
Hybrid Regularizations for Multi-Aspect Category Sentiment Analysis,
AffCom(14), No. 4, October 2023, pp. 3294-3304.
IEEE DOI 2312
BibRef

Hu, M.T.[Meng-Ting], Gao, H.[Hang], Wu, Y.[Yike], Su, Z.[Zhong], Zhao, S.[Shiwan],
Fine-Grained Domain Adaptation for Aspect Category Level Sentiment Analysis,
AffCom(14), No. 4, October 2023, pp. 2839-2850.
IEEE DOI 2312
BibRef

Wang, Y.[Yuan], Huo, P.[Peng], Tang, L.Y.[Ling-Yan], Xiong, N.[Ning], Hu, M.T.[Meng-Ting], Yu, Q.[Qi], Yang, J.[Jucheng],
Modeling Category Semantic and Sentiment Knowledge for Aspect-Level Sentiment Analysis,
AffCom(15), No. 4, October 2024, pp. 1962-1969.
IEEE DOI 2412
Task analysis, Semantics, Sentiment analysis, Multitasking, Vectors, Correlation, Convolution, Aspect-level sentiment analysis, multi-task learning 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

Zhang, B.[Bowen], Fu, X.H.[Xiang-Hua], Luo, C.[Chuyao], Ye, Y.M.[Yun-Ming], Li, X.[Xutao], Jing, L.W.[Li-Wen],
Cross-Domain Aspect-Based Sentiment Classification by Exploiting Domain- Invariant Semantic-Primary Feature,
AffCom(14), No. 4, October 2023, pp. 3106-3119.
IEEE DOI 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

Ji, X.Y.[Xiao-Yue], Dong, Z.[Zhekang], Han, Y.F.[Yi-Feng], Lai, C.S.[Chun Sing], Qi, D.L.[Dong-Lian],
A Brain-Inspired Hierarchical Interactive In-Memory Computing System and Its Application in Video Sentiment Analysis,
CirSysVideo(33), No. 12, December 2023, pp. 7928-7942.
IEEE DOI 2312
BibRef

Liu, J.Y.[Jing-Yi], Li, S.[Sheng],
A dependency-based hybrid deep learning framework for target-dependent sentiment classification,
PRL(176), 2023, pp. 160-166.
Elsevier DOI 2312
Target-dependent sentiment classification, Dependency parsing, Text filtering, Data preprocess 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

Wang, B.L.[Bing-Lu], Yang, K.[Kang], Zhao, Y.Q.[Yong-Qiang], Long, T.[Teng], Li, X.L.[Xue-Long],
Prototype-Based Intent Perception,
MultMed(25), 2023, pp. 8308-8319.
IEEE DOI 2312
understand the intention of images. 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

Prakash, V.J.[V. Jothi], Vijay, S.A.A.[S. Arul Antran],
A multi-aspect framework for explainable sentiment analysis,
PRL(178), 2024, pp. 122-129.
Elsevier DOI 2402
Explainable sentiment analysis, Multi-aspect framework, Aspect extraction, Hierarchical neural networks, Natural language processing 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

Luo, Y.T.[Yu-Tong], Zhong, X.Y.[Xin-Yue], Zeng, M.[Minchen], Xie, J.L.[Jia-Lan], Wang, S.Y.[Shi-Yuan], Liu, G.Y.[Guang-Yuan],
CGLF-Net: Image Emotion Recognition Network by Combining Global Self-Attention Features and Local Multiscale Features,
MultMed(26), 2024, pp. 1894-1908.
IEEE DOI 2402
Feature extraction, Emotion recognition, Transformers, Visualization, Image recognition, Data mining, self-attention 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

Babanejad, N.[Nastaran], Davoudi, H.[Heidar], Agrawal, A.[Ameeta], An, A.[Aijun], Papagelis, M.[Manos],
The Role of Preprocessing for Word Representation Learning in Affective Tasks,
AffCom(15), No. 1, January 2024, pp. 254-272.
IEEE DOI 2403
Task analysis, Sentiment analysis, Analytical models, Training, Context modeling, Buildings, Syntactics, Affective tasks, word representation BibRef

Ruan, S.[Shulan], Zhang, K.[Kun], Wu, L.[Le], Xu, T.[Tong], Liu, Q.[Qi], Chen, E.[Enhong],
Color Enhanced Cross Correlation Net for Image Sentiment Analysis,
MultMed(26), 2024, pp. 4097-4109.
IEEE DOI 2403
Image color analysis, Sentiment analysis, Feature extraction, Correlation, Visualization, Brain modeling, Analytical models, feature representation BibRef

Kim, J.Y.[Jin-Young], Ko, Y.J.[Young-Joong],
SPACE: Senti-Prompt As Classifying Embedding for sentiment analysis,
PRL(180), 2024, pp. 62-67.
Elsevier DOI 2404
Sentiment analysis, Prompt-tuning, Representation learning, Attention pattern BibRef

Wang, Y.J.[Ya-Jie], Chen, M.[Mulin], Li, X.L.[Xue-Long],
Continuous Emotion-Based Image-to-Music Generation,
MultMed(26), 2024, pp. 5670-5679.
IEEE DOI 2404
Task analysis, Music, Distance measurement, Annotations, Training, Standards, vicinagearth security 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

Shi, Q.H.[Qing-HongYa], Ye, M.[Mang], Huang, W.K.[Wen-Ke], Ruan, W.J.[Wei-Jian], Du, B.[Bo],
Label-Aware Calibration and Relation-Preserving in Visual Intention Understanding,
IP(33), 2024, pp. 2627-2638.
IEEE DOI Code:
WWW Link. 2404
Intention behind the images in social media. Visualization, Task analysis, Calibration, Correlation, Image classification, Data augmentation, intention relation 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

Anas, M.[Mohammad], Saiyeda, A.[Anam], Sohail, S.S.[Shahab Saquib], Cambria, E.[Erik], Hussain, A.[Amir],
Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms?,
IEEE_Int_Sys(39), No. 2, March 2024, pp. 5-10.
IEEE DOI 2405
Deep learning, Generative AI, Analytical models, Context modeling, Chatbots, 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

Tang, X.Y.[Xiang-Yun], Liao, D.L.[Dong-Liang], Shen, M.[Meng], Zhu, L.H.[Lie-Huang], Huang, S.[Shen], Li, G.[Gongfu], Man, H.[Hong], Xu, J.[Jin],
Confidence-Aware Sentiment Quantification via Sentiment Perturbation Modeling,
AffCom(15), No. 2, April 2024, pp. 736-750.
IEEE DOI 2406
Perturbation methods, Sentiment analysis, Task analysis, Fake news, Semantics, Feature extraction, Analytical models, sentiment quantification BibRef

Yuan, L.[Li], Wang, J.[Jin], Yu, L.C.[Liang-Chih], Zhang, X.J.[Xue-Jie],
Encoding Syntactic Information into Transformers for Aspect-Based Sentiment Triplet Extraction,
AffCom(15), No. 2, April 2024, pp. 722-735.
IEEE DOI 2406
Task analysis, Syntactics, Data mining, Tagging, Pipelines, Transformers, Sentiment analysis, transformers 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

Zeng, Y.S.[Yu-Shi], Wang, G.H.[Guo-Hua], Ren, H.P.[Hao-Peng], Cai, Y.[Yi], Leung, H.F.[Ho-Fung], Li, Q.[Qing], Huang, Q.[Qingbao],
A Knowledge-Enhanced and Topic-Guided Domain Adaptation Model for Aspect-Based Sentiment Analysis,
AffCom(15), No. 2, April 2024, pp. 709-721.
IEEE DOI 2406
Syntactics, Feature extraction, Task analysis, Sentiment analysis, Adaptation models, Portable computers, Knowledge graphs, cross-domain BibRef

Wang, Y.[Yu], Zhou, S.P.[Shun-Ping], Guan, Q.F.[Qing-Feng], Fang, F.[Fang], Yang, N.[Ni], Li, K.L.[Kang-Lin], Liu, Y.Y.[Yuan-Yuan],
Enhancing Place Emotion Analysis with Multi-View Emotion Recognition from Geo-Tagged Photos: A Global Tourist Attraction Perspective,
IJGI(13), No. 7, 2024, pp. 256.
DOI Link 2408
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

Diwali, A.[Arwa], Saeedi, K.[Kawther], Dashtipour, K.[Kia], Gogate, M.[Mandar], Cambria, E.[Erik], Hussain, A.[Amir],
Sentiment Analysis Meets Explainable Artificial Intelligence: A Survey on Explainable Sentiment Analysis,
AffCom(15), No. 3, July 2024, pp. 837-846.
IEEE DOI 2409
Sentiment analysis, Analytical models, Computational modeling, Task analysis, Deep learning, Predictive models, interpretability 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

Cen, J.L.[Jing-Lun], Qing, C.M.[Chun-Mei], Ou, H.[Haochun], Xu, X.M.[Xiang-Min], Tan, J.P.[Jun-Peng],
MASANet: Multi-Aspect Semantic Auxiliary Network for Visual Sentiment Analysis,
AffCom(15), No. 3, July 2024, pp. 1439-1450.
IEEE DOI 2409
Visualization, Semantics, Sentiment analysis, Task analysis, Feature extraction, Affective computing, semantic auxiliary 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

Watanabe, S.[Shuhei], Horiuchi, T.[Takahiko],
Layered Modeling of Affective, Perception, and Visual Properties: Optimizing Structure With Genetic Algorithm,
HMS(54), No. 5, October 2024, pp. 609-618.
IEEE DOI 2410
Mathematical models, Visualization, Genetic algorithms, Correlation, Computational modeling, Numerical analysis, perception 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

Liu, L.[Lulin], Qin, T.[Tao], Zhou, Y.K.[Yuan-Kun], Wang, C.X.[Chen-Xu], Guan, X.H.[Xiao-Hong],
SynSem-ASTE: An Enhanced Multi-Encoder Network for Aspect Sentiment Triplet Extraction With Syntax and Semantics,
AffCom(15), No. 4, October 2024, pp. 2097-2111.
IEEE DOI 2412
Syntactics, Semantics, Task analysis, Tagging, Feature extraction, Sentiment analysis, Pipelines, Aspect-based sentiment analysis, cross attention 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

Gao, A.[Anqi], Zhong, Y.[Yantao],
Product Color Design Concept that Considers Human Emotion Perception: Based on Deep Learning and Cluster Analysis,
IET-Bio(2024), No. 1, 2024, pp. 5576927.
DOI Link 2501
clustering analysis, emotional color, style fusion, transfer learning BibRef

Zhang, J.[Jing], Zheng, L.[Liang], Wang, M.[Meng], Guo, D.[Dan],
Training A Small Emotional Vision Language Model for Visual Art Comprehension,
ECCV24(LXVII: 397-413).
Springer DOI 2412
BibRef

Darraz, N.[Nossayba], Karabila, I.[Ikram], El-Ansari, A.[Anas], Alami, N.[Nabil], Chenouni, S.[Salma], El Mallahi, M.[Mostafa],
Improving Hybrid Recommendations with VADER-Powered Sentiment Analysis*,
ISCV24(1-7)
IEEE DOI 2408
Sentiment analysis, Reviews, Filtering, Computational modeling, User-generated content, Transforms, Root mean square, Lasso BibRef

Akallal, Y.[Yassine], Hdioud, B.[Boutaina.], Thami, R.O.H.[Rachid. Oulad Haj],
Content and link Analysis of a Moroccan entrepreneurs group,
ISCV24(1-8)
IEEE DOI 2408
Sentiment analysis, Analytical models, Social networking (online), Intelligent systems BibRef

Kojima, B.[Banri], Komamizu, T.[Takahiro], Kawanishi, Y.[Yasutomo], Doman, K.[Keisuke], Ide, I.[Ichiro],
Image Impression Estimation by Clustering People with Similar Tastes,
MVA23(1-5)
DOI Link 2403
Annotations, Machine vision, Estimation, Training data, Explosions BibRef

Weng, S.[Shuchen], Zhang, P.X.[Pei-Xuan], Chang, Z.[Zheng], Wang, X.L.[Xin-Long], Li, S.[Si], Shi, B.X.[Bo-Xin],
Affective Image Filter: Reflecting Emotions from Text to Images,
ICCV23(10776-10785)
IEEE DOI 2401
BibRef

Kim, S.[Seoyun], An, C.[ChaeHee], Cha, J.[Junyeop], Kim, D.J.[Dong-Jae], Park, E.[Eunil],
D-ViSA: A Dataset for Detecting Visual Sentiment from Art Images,
ASI23(3043-3051)
IEEE DOI Code:
WWW Link. 2401
BibRef

Tong, S.[Song], Duan, J.Y.[Jing-Yi], Liang, X.F.[Xue-Feng], Kumada, T.[Takatsune], Peng, K.[Kaiping], Nakashima, R.[Ryoichi],
Inferring Affective Experience from the Big Picture Metaphor: A Two-dimensional Visual Breadth Model,
ABAW23(5880-5888)
IEEE DOI 2309
BibRef

Feng, T.L.[Ting-Lei], Liu, J.X.[Jia-Xuan], Yang, J.F.[Ju-Feng],
Probing Sentiment-Oriented PreTraining Inspired by Human Sentiment Perception Mechanism,
CVPR23(2850-2860)
IEEE DOI 2309
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

Lu, M.L.[Meng-Lin], Zhao, T.Z.[Tong-Zhou], Mao, C.B.[Cheng-Bo], Wang, H.[Huibo],
Target-level Sentiment Analysis Based on Image and Text Fusion,
ICRVC22(305-309)
IEEE DOI 2301
Sentiment analysis, Visualization, Analytical models, Fuses, Splicing, Bit error rate, Feature extraction, attention mechanism BibRef

Wang, X.[Xue], Liu, P.[Peiyu], Zhu, Z.F.[Zhen-Fang], Lu, R.[Ran],
Aspect-based Sentiment Analysis with Graph Convolutional Networks over Dependency Awareness,
ICPR22(2238-2245)
IEEE DOI 2212
Sentiment analysis, Analytical models, Semantics, Benchmark testing, Graph neural networks, Grammar BibRef

Yuan, X.W.[Xiao-Wei], Hu, J.Y.[Jing-Yuan], Zhang, X.D.[Xiao-Dan], Lv, H.L.[Hong-Lei],
Pay attention to emoji: Feature Fusion Network with EmoGraph2vec Model for Sentiment Analysis,
ICPR22(1529-1535)
IEEE DOI 2212
Representation learning, Sentiment analysis, Analytical models, Computational modeling, Semantics, Neural networks, Knowledge based systems BibRef

Zhu, W.[Wei], Zheng, Z.H.[Zi-He], Zheng, H.[Haitian], Lyu, H.[Hanjia], Luo, J.B.[Jie-Bo],
Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis,
ICPR22(571-577)
IEEE DOI 2212
Training, Learning systems, Visualization, Sentiment analysis, Aggregates, Neural networks, Prototypes BibRef

Jin, L.[Lingbin], Zhang, L.[Li],
Discriminant Variance Criterion for Sentiment Analysis,
ICPR22(3056-3062)
IEEE DOI 2212
Support vector machines, Sentiment analysis, Semantics, Feature extraction, Information filters, Logistics 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

Trivedi, A.K.[Ashutosh Kumar], Tiwari, A.[Abhishek], Saha, S.[Sriparna], Maitra, A.[Anutosh], Ramnani, R.[Roshni], Sengupta, S.[Shubhashis],
Towards Sentiment and Emotion aided Intent Detection,
ICPR22(2510-2516)
IEEE DOI 2212
Learning systems, Emotion recognition, Correlation, Semantics, Tagging, Feature extraction, Multitasking BibRef

Ye, Y.R.[Ying-Rui], Moroto, Y.[Yuya], Maeda, K.[Keisuke], Ogawa, T.[Takahiro], Haseyama, M.[Miki],
Visual Sentiment Prediction Using Cross-Way Few-Shot Learning Based on Knowledge Distillation,
ICIP22(3838-3842)
IEEE DOI 2211
Training, Visualization, Training data, Predictive models, Robustness, Task analysis, Visual sentiment prediction, sentiment theory BibRef

Tliba, M.[Marouane], Kerkouri, M.A.[Mohamed Amine], Chetouani, A.[Aladine], Bruno, A.[Alessandro],
Self Supervised Scanpath Prediction Framework for Painting Images,
Ego4D-EPIC22(1538-1547)
IEEE DOI 2210
Visualization, Self-supervised learning, Predictive models, Observers, Quality assessment, Task analysis BibRef

Aslan, S.[Sinem], Castellano, G.[Giovanna], Digeno, V.[Vincenzo], Migailo, G.[Giuseppe], Scaringi, R.[Raffaele], Vessio, G.[Gennaro],
Recognizing the Emotions Evoked by Artworks Through Visual Features and Knowledge Graph-Embeddings,
FAPER22(129-140).
Springer DOI 2208
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Bounab, Y.[Yazid], Oussalah, M.[Mourad], Beddiar, D.R.[Djamila Romaissa],
Impact of Quality Of Images On Users Behavior On Social Media,
IPTA20(1-6)
IEEE DOI 2206
Image quality, Correlation, Social networking (online), Web services, Web 2.0, Tourism industry, Indeexes, social media, sentiments 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
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Bianconi, F., Filippucci, M., Seccaroni, M., Aquinardi, C.M.,
Urban Parametric Perception. the Case Study of the Historic Centre Of Perugia,
ISPRS21(B2-2021: 839-846).
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Eye tracking, EEG analysis. BibRef

Liang, Y.[Yun], Maeda, K.[Keisuke], Ogawa, T.[Takahiro], Haseyama, M.[Miki],
Deep Metric Network Via Heterogeneous Semantics for Image Sentiment Analysis,
ICIP21(1039-1043)
IEEE DOI 2201
Measurement, Sentiment analysis, Visualization, Correlation, Design methodology, Semantics, Deep metric learning, heterogeneous semantics BibRef

Can, O.[Ogul], Gürbüz, Y.Z.[Yeti Z.], Alatan, A.A.[A. Aydvn],
Deep Metric Learning With Alternating Projections Onto Feasible Sets,
ICIP21(1264-1268)
IEEE DOI 2201
Measurement, Systematics, Image processing, Image retrieval, Training data, Benchmark testing, Metric learning, projections BibRef

Karaman, K.[Kaan], Alatan, A.A.[A. Aydin],
Metu Loss: Metric Learning With Entangled Triplet Unified Loss,
ICIP21(1279-1283)
IEEE DOI 2201
Measurement, Potential energy, Extraterrestrial phenomena, Image processing, Semantics, Image retrieval, Deep metric learning, image retrieval BibRef

Maqbool, H.[Hira], Masek, M.[Martin],
Image Aesthetics Classification using Deep Features and Image Category,
IVCNZ21(1-5)
IEEE DOI 2201
Deep learning, Industries, Visualization, Automation, Lighting, Manuals, Feature extraction, Image aesthetics, deep learning BibRef

Lian, T.[Tianpei], Cao, Z.G.[Zhi-Guo], Xian, K.[Ke], Pan, Z.Y.[Zhi-Yu], Zhong, W.C.[Wei-Cai],
Context-Aware Candidates for Image Cropping,
ICIP21(1479-1483)
IEEE DOI 2201
Convolution, Image processing, Manuals, Real-time systems, Image cropping, fully convolution regression network, aesthetic quality BibRef

Yeo, Y.Y.[Yong-Yaw], See, J.[John], Wong, L.K.[Lai-Kuan], Goh, H.N.[Hui-Ngo],
Generating Aesthetic Based Critique for Photographs,
ICIP21(2523-2527)
IEEE DOI 2201
Measurement, Deep learning, Image processing, Semantics, Decoding, Task analysis, Image captioning, aesthetic quality assessment, Word Mover's Distance BibRef

Lian, T.[Tianpei], Cao, Z.G.[Zhi-Guo], Lu, H.[Hao], Wu, Z.J.[Zi-Jin], Zhong, W.C.[Wei-Cai],
Image Cropping Assisted By Modeling Inter-Patch Relations,
ICIP21(2573-2577)
IEEE DOI 2201
Convolution, Image edge detection, Logic gates, Feature extraction, Task analysis, Faces, Image cropping, aesthetic quality, edge information BibRef

Su, N.M.[Norman Makoto], Crandall, D.J.[David J.],
The Affective Growth of Computer Vision,
CVPR21(9287-9296)
IEEE DOI 2111
Deep learning, Standards, Strain BibRef

Singh, J.[Jaskirat], Zheng, L.[Liang],
Combining Semantic Guidance and Deep Reinforcement Learning For Generating Human Level Paintings,
CVPR21(16382-16391)
IEEE DOI 2111
Backpropagation, Training, Semantics, Pipelines, Reinforcement learning, Stroke (medical condition) BibRef

Hong, C.Y.[Chao-Yi], Du, S.Y.[Shuai-Yuan], Xian, K.[Ke], Lu, H.[Hao], Cao, Z.G.[Zhi-Guo], Zhong, W.[Weicai],
Composing Photos Like a Photographer,
CVPR21(7053-7062)
IEEE DOI 2111
Photography, Computational modeling, Benchmark testing BibRef

Mittal, T.[Trisha], Mathur, P.[Puneet], Bera, A.[Aniket], Manocha, D.[Dinesh],
Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causality,
CVPR21(5657-5667)
IEEE DOI 2111
Learning systems, Visualization, Computational modeling, Motion pictures, Facial features BibRef

Zhang, Y.M.[Yi-Meng], Zhang, Y.[Yang], Gao, J.J.[Jiao-Jiao],
The Influence of the Aesthetic Design of Taobao APP on Users' Emotional Experience,
DHM21(II:403-414).
Springer DOI 2108
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Kayatani, Y.[Yuta], Yang, Z.K.[Ze-Kun], Otani, M.[Mayu], Garcia, N.[Noa], Chu, C.[Chenhui], Nakashima, Y.[Yuta], Takemura, H.[Haruo],
The Laughing Machine: Predicting Humor in Video,
WACV21(2072-2081)
IEEE DOI 2106
Visualization, TV, Computational modeling, Face recognition, Predictive models 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
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Zhang, H., Zhang, M.,
Research on Cyberpunk Images in the Visual Digital Media,
CVIDL20(39-43)
IEEE DOI 2102
art, computer literacy, cultural aspects, educational administrative data processing, human factors, visual digital media BibRef

Du, J., Li, T.,
The Establishment of Color Proportion and Color Schemes Database of Shaanxi Fengxiang Wood Engraving New Year Painting,
CVIDL20(305-312)
IEEE DOI 2102
art, image colour analysis, image representation, image scanners, wood, color schemes database, color value data, color database BibRef

Ching, J.H., See, J., Wong, L.K.,
Learning Image Aesthetics by Learning Inpainting,
ICIP20(2246-2250)
IEEE DOI 2011
Task analysis, Visualization, Loss measurement, Machine learning, Generative adversarial networks, Generators, Feature extraction, photographic rules BibRef

Newman, A.[Anelise], Fosco, C.[Camilo], Casser, V.[Vincent], Lee, A.[Allen], McNamara, B.[Barry], Oliva, A.[Aude],
Multimodal Memorability: Modeling Effects of Semantics and Decay on Video Memorability,
ECCV20(XVI: 223-240).
Springer DOI 2010
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Yang, C., Kong, L.,
Research on Product Style Design Based on Genetic Algorithm,
ICIVC20(317-321)
IEEE DOI 2009
Product design, Genetic algorithms, Sociology, Statistics, Feature extraction, Fatigue, stylized design, genetic algorithm, co-evolution BibRef

Pilli, S., Patwardhan, M., Pedanekar, N., Karande, S.,
Predicting Sentiments in Image Advertisements using Semantic Relations among Sentiment Labels,
EmotioNet20(1640-1648)
IEEE DOI 2008
Semantics, Convolution, Measurement, Feature extraction, Mathematical model, Neural networks, Visualization BibRef

Polanía, L.F., Flores, M., Nokleby, M., Li, Y.,
Learning Furniture Compatibility with Graph Neural Networks,
WiCV20(1505-1513)
IEEE DOI 2008
Feature extraction, Computational modeling, Data models, Neural networks, Logic gates, Task analysis BibRef

Li, D., Zhang, J., Huang, K., Yang, M.,
Composing Good Shots by Exploiting Mutual Relations,
CVPR20(4212-4221)
IEEE DOI 2008
Feature extraction, Logic gates, Predictive models, Convolution, Cognition, Task analysis, Correlation BibRef

Chen, Q., Zhang, W., Zhou, N., Lei, P., Xu, Y., Zheng, Y., Fan, J.,
Adaptive Fractional Dilated Convolution Network for Image Aesthetics Assessment,
CVPR20(14102-14111)
IEEE DOI 2008
Kernel, Convolution, Training, Machine learning, Interpolation, Task analysis, Libraries BibRef

Liu, D., Puri, R., Kamath, N., Bhattacharya, S.,
Composition-Aware Image Aesthetics Assessment,
WACV20(3558-3567)
IEEE DOI 2006
Visualization, Convolution, Computational modeling, Cognition, Image edge detection, Task analysis, Integrated circuits BibRef

Ghosal, K., Rana, A., Smolic, A.,
Aesthetic Image Captioning From Weakly-Labelled Photographs,
CroMoL19(4550-4560)
IEEE DOI 2004
convolutional neural nets, feature extraction, image annotation, image filtering, Internet, photography, probability, Noisy Data BibRef

Kastner, M.A.[Marc A.], Ide, I.[Ichiro], Kawanishi, Y.[Yasutomo], Hirayama, T.[Takatsugu], Deguchi, D.[Daisuke], Murase, H.[Hiroshi],
Browsing Visual Sentiment Datasets Using Psycholinguistic Groundings,
MMMod20(II:697-702).
Springer DOI 2003
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Li, Z.Q.[Zheng-Qing], Zha, Z.J.[Zheng-Jun], Cao, Y.[Yang],
Deep Palette-based Color Decomposition for Image Recoloring with Aesthetic Suggestion,
MMMod20(I:127-138).
Springer DOI 2003
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Al-Halah, Z., Aitken, A., Shi, W., Caballero, J.,
Smile, Be Happy :) Emoji Embedding for Visual Sentiment Analysis,
CroMoL19(4491-4500)
IEEE DOI 2004
data analysis, data visualisation, image classification, learning (artificial intelligence), neural nets, transfer learning BibRef

Shen, X.[Xi], Efros, A.A.[Alexei A.], Aubry, M.[Mathieu],
Discovering Visual Patterns in Art Collections With Spatially-Consistent Feature Learning,
CVPR19(9270-9279).
IEEE DOI 2002
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Huang, C.[Chong], Lin, C.E.[Chuan-En], Yang, Z.Y.[Zhen-Yu], Kong, Y.[Yan], Chen, P.[Peng], Yang, X.[Xin], Cheng, K.T.[Kwang-Ting],
Learning to Film From Professional Human Motion Videos,
CVPR19(4239-4248).
IEEE DOI 2002
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Hosu, V.[Vlad], Goldlucke, B.[Bastian], Saupe, D.[Dietmar],
Effective Aesthetics Prediction With Multi-Level Spatially Pooled Features,
CVPR19(9367-9375).
IEEE DOI 2002
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Ye, J.[Jin], Peng, X.J.[Xiao-Jiang], Qiao, Y.[Yu], Xing, H.[Hao], Li, J.L.[Jun-Li], Ji, R.R.[Rong-Rong],
Visual-Textual Sentiment Analysis in Product Reviews,
ICIP19(869-873)
IEEE DOI 1910
sentiment analysis, product reviews, tucker decomposition, DTF BibRef

Wang, W.N.[Wei-Ning], Su, J.J.[Jun-Jie], Li, L.M.[Le-Min], Xu, X.M.[Xiang-Min], Luo, J.B.[Jie-Bo],
Meta-Learning Perspective for Personalized Image Aesthetics Assessment,
ICIP19(1875-1879)
IEEE DOI 1910
Image Aesthetics, Personalized Preference, Meta-Learning, Meta regularization, Deep Learning BibRef

Zhang, W., Zhai, G., Yang, X., Yan, J.,
Hierarchical Features Fusion for Image Aesthetics Assessment,
ICIP19(3771-3775)
IEEE DOI 1910
Image Aesthetics Assessment, Low-rank Bilinear Pooling, Hierarchical Features BibRef

Yu, J., Cui, C., Geng, L., Ma, Y., Yin, Y.,
Towards Unified Aesthetics and Emotion Prediction in Images,
ICIP19(2526-2530)
IEEE DOI 1910
Aesthetics assessment, emotion recognition, multi-task learning BibRef

Wang, W., Deng, R.,
Modeling Human Perception for Image Aesthetic Assessment,
ICIP19(1029-1033)
IEEE DOI 1910
Image Aesthetic Assessment, Deep Neural Network, Attractive Region, Adaptive Aggregation BibRef

Rodríguez-Pardo, C.[Carlos], Bilen, H.[Hakan],
Personalised Aesthetics with Residual Adapters,
IbPRIA19(I:508-520).
Springer DOI 1910
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Felicetti, A.[Andrea], Martini, M.[Massimo], Paolanti, M.[Marina], Pierdicca, R.[Roberto], Frontoni, E.[Emanuele], Zingaretti, P.[Primo],
Visual and Textual Sentiment Analysis of Daily News Social Media Images by Deep Learning,
CIAP19(I:477-487).
Springer DOI 1909
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Stefanini, M.[Matteo], Cornia, M.[Marcella], Baraldi, L.[Lorenzo], Corsini, M.[Massimiliano], Cucchiara, R.[Rita],
Artpedia: A New Visual-Semantic Dataset with Visual and Contextual Sentences in the Artistic Domain,
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Offert, F.[Fabian],
Images of Image Machines. Visual Interpretability in Computer Vision for Art,
CVAA18(II:710-715).
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Garcia, N.[Noa], Vogiatzis, G.[George],
How to Read Paintings: Semantic Art Understanding with Multi-modal Retrieval,
CVAA18(II:676-691).
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Gonthier, N.[Nicolas], Gousseau, Y.[Yann], Ladjal, S.[Said], Bonfait, O.[Olivier],
Weakly Supervised Object Detection in Artworks,
CVAA18(II:692-709).
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Cianci, M.G., Molinari, M.,
Information Modeling and Landscape: Intervention Methodology For Reading Complex Systems,
3DARCH19(269-276).
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Aesthetics of landscapes. BibRef

Ma, N., Volkov, A., Livshits, A., Pietrusinski, P., Hu, H., Bolin, M.,
An Universal Image Attractiveness Ranking Framework,
WACV19(657-665)
IEEE DOI 1904
image classification, image retrieval, indexing, learning (artificial intelligence), neural nets, search engines, Indexes BibRef

Saito, J.[Junki], Nakamura, S.[Satoshi],
Fontender: Interactive Japanese Text Design with Dynamic Font Fusion Method for Comics,
MMMod19(II:554-559).
Springer DOI 1901
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Image Aesthetics Assessment Using Fully Convolutional Neural Networks,
MMMod19(I:361-373).
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Wei, Z., Zhang, J., Shen, X., Lin, Z., Mech, R., Hoai, M., Samaras, D.,
Good View Hunting: Learning Photo Composition from Dense View Pairs,
CVPR18(5437-5446)
IEEE DOI 1812
Proposals, Training, Agriculture, Task analysis, Knowledge transfer, Protocols, Virtual private networks BibRef

Liu, W., Fu, X.,
Introduce More Characteristics of Samples into Cross-domain Sentiment Classification,
ICPR18(25-30)
IEEE DOI 1812
Training, Adaptation models, Neural networks, Task analysis, Training data, Mathematical model, Data models BibRef

Fan, S., Shen, Z., Jiang, M., Koenig, B.L., Xu, J., Kankanhalli, M.S., Zhao, Q.,
Emotional Attention: A Study of Image Sentiment and Visual Attention,
CVPR18(7521-7531)
IEEE DOI 1812
Semantics, Visualization, Computational modeling, Observers, Neural networks, Benchmark testing, Image annotation BibRef

Paolanti, M.[Marina], Kaiser, C.[Carolin], Schallner, R.[René], Frontoni, E.[Emanuele], Zingaretti, P.[Primo],
Visual and Textual Sentiment Analysis of Brand-Related Social Media Pictures Using Deep Convolutional Neural Networks,
CIAP17(I:402-413).
Springer DOI 1711
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

Wu, L., Liu, S., Jian, M., Luo, J., Zhang, X., Qi, M.,
Reducing noisy labels in weakly labeled data for visual sentiment analysis,
ICIP17(1322-1326)
IEEE DOI 1803
Indexes, Visual sentiment analysis, deep learning, mislabeled images, sentiment conflict BibRef

Chen, X., Wang, Y., Liu, Q.,
Visual and textual sentiment analysis using deep fusion convolutional neural networks,
ICIP17(1557-1561)
IEEE DOI 1803
Convolutional neural networks, Feature extraction, Semantics, Sentiment analysis, Social network services, Training, visual sentiment BibRef

Zheng, H., Chen, T., You, Q., Luo, J.,
When saliency meets sentiment: Understanding how image content invokes emotion and sentiment,
ICIP17(630-634)
IEEE DOI 1803
Analytical models, Computational modeling, Correlation, Proposals, Saliency detection, Sentiment analysis, Visualization, saliency, sentiment perception BibRef

Niu, T.[Teng], Zhu, S.[Shiai], Pang, L.[Lei], El Saddik, A.[Abdulmotaleb],
Sentiment Analysis on Multi-View Social Data,
MMMod16(II: 15-27).
Springer DOI 1601
BibRef

Shin, A.[Andrew], Ushiku, Y.[Yoshitaka], Harada, T.[Tatsuya],
Image Captioning with Sentiment Terms via Weakly-Supervised Sentiment Dataset,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Sartori, A.[Andreza], Senyazar, B.[Berhan], Salah, A.A.A.[Alkim Almila Akdag], Salah, A.A.[Albert Ali], Sebe, N.[Nicu],
Emotions in Abstract Art: Does Texture Matter?,
CIAP15(I:671-682).
Springer DOI 1511
BibRef

Kang, D.W.[Dong-Wann], Shim, H.[Hyounoh], Yoon, K.[Kyunghyun],
Mood from painting: Estimating the mood of painting by using color image scale,
FCV15(1-4)
IEEE DOI 1506
art BibRef

Gbèhounou, S.[Syntyche], Lecellier, F.[François],
Can Salient Interest Regions Resume Emotional Impact of an Image?,
CAIP13(515-522).
Springer DOI 1308
BibRef

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