Our survey 'Recent Trends of Multimodal Affective Computing: A Survey from NLP Perspective' has released link: https://arxiv.org/abs/2409.07388
- Multimodal Sentiment Analysis
- Multimodal Emotion Recognition in Conversation
- Multimodal Aspect-based Sentiment Analysis
- Multimodal Multi-label Emotion Recognition
- Multimodal Emotion-cause Pair Extraction in Conversation
We will release a review of multimodal affective computing soon
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[1] Huisheng Mao, Baozheng Zhang, Hua Xu, Ziqi Yuan, Yihe Liu. [Robust-MSA: Understanding the Impact of Modality Noise on Multimodal Sentiment Analysis]
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[2] S Afzal, HA Khan, IU Khan, MJ Piran…. [A Comprehensive Survey on Affective Computing Challenges, Trends, Applications, and Future Directions_]
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[3] J Peng, T Wu, W Zhang, F Cheng, S Tan, F Yi…. [A fine-grained modal label-based multi-stage network for multimodal sentiment analysis]
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[4] Y Zhi, J Li, H Wang, J Chen…. [A Fine-Grained Tri-Modal Interaction Model for Multimodal Sentiment Analysis]
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[5] J LIU, H SONG, DP CHEN, B WANG, ZW ZHANG. [A Multimodal Sentiment Analysis Model Enhanced with Non-verbal Information and Contrastive Learning]
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[6] X Sun, X Ren, X Xie. [A NOVEL MULTIMODAL SENTIMENT ANALYSIS MODEL BASED ON GATED FUSION AND MULTI-TASK LEARNING]
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[7] MM Amin, R Mao, E Cambria, BW Schuller. [A Wide Evaluation of ChatGPT on Affective Computing Tasks]
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[8] AAB Zadeh, PP Liang, S Poria, E Cambria…. [CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph]
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[9] W Yu, H Xu, F Meng, Y Zhu, Y Ma, J Wu…. [A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotations of Modality]
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[10] K Kim, S Park. [All-modalities-in-One BERT for multimodal sentiment analysis]
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[11] Hui Ma, Jian Wang, Hongfei Lin, Bo Zhang, Yijia Zhang, Bo Xu. [A_Transformer-Based_Model_With_Self-Distillation_for_Multimodal_Emotion_Recognition_in_Conversations]
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[12] J Tang, D Liu, X Jin, Y Peng, Q Zhao…. [Bi-Direction Attention Based Fusion Network for Multimodal Sentiment Analysis]
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[13] Z Li, B Xu, C Zhu, T Zhao. [CLMLF-A Contrastive Learning and Multi-Layer Fusion Method for Multimodal Sentiment Detection]
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[14] J Yang, Y Yu, D Niu, W Guo, Y Xu. [Contrastive Feature Decomposition for Multimodal Sentiment Analysis]
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[15] Y Yu, M Zhao, S Qi, F Sun, B Wang, W Guo…. [Contrastive Knowledge Injection for Multimodal Sentiment Analysis]
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[16] DS Chauhan, MS Akhtar, A Ekbal…. [Context-aware Interactive Attention for Multi-modal Sentiment and Emotion Analysis]
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[17] M Huang, C Qing, J Tan, X Xu. [Context-Based Adaptive Multimodal Fusion Network for Continuous Frame-Level Sentiment Prediction]
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[18] Y Zeng, W Yan, S Mai, H Hu. [Disentanglement Translation Network for multimodal sentiment analysis]
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[19] S Mai, H Hu, S Xing. [Hierarchical Feature Fusion Network with Local and Global Perspectives for Multimodal Affective Computing]
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[20] Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih. [Multimodal Phased Transformer for Sentiment Analysis]
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[21] A Martins, R Astudillo. [A Sparse Model of Attention and Multi-Label Classification]
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[22] H Liang, W Xie, X He, S Song…. [GUIDED CIRCULAR DECOMPOSITION AND CROSS-MODAL RECOMBINATION FOR MULTIMODAL SENTIMENT ANALYSIS]
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[23] S Mai, Y Zeng, S Zheng, H Hu. [Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysis]
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[24] X Zhao, Y Chen, W Li, L Gao…. [An Extended Multimodal Adaptation Gate for Multimodal Sentiment Analysis]
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[25] D Hazarika, S Poria, R Mihalcea…. [Interactive Conversational Memory Network for Multimodal Emotion Detection]
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[26] C Busso, M Bulut, CC Lee, A Kazemzadeh…. [Interactive emotional dyadic motion capture database]
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[27] W Han, H Chen, S Poria. [Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis]
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[28] W Rahman, MK Hasan, S Lee, A Zadeh…. [Integrating Multimodal Information in Large Pretrained Transformers]
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[29] C Chen, H Hong, J Guo, B Song. [Inter-Intra Modal Representation Augmentation With Trimodal Collaborative Disentanglement Network for Multimodal Sentiment Analysis]
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[30] VW Liang, Y Zhang, Y Kwon…. [Understanding the Modality Gap in Multi-modal Contrastive Representation Learning]
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[31] D Hazarika, R Zimmermann, S Poria. [Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysis]
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[32] J Zeng, J Zhou, T Liu. [Mitigating Inconsistencies in Multimodal Sentiment Analysis under Uncertain Missing Modalities]
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[33] K Yang, H Xu, K Gao. [Cross-Modal BERT for Text-Audio Sentiment Analysis]
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[34] S Mai, H Hu, S Xing. [Modality to Modality Translation An Adversarial Representation Learning and Graph Fusion Network for Multimodal Fusion]
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[35] Z Liu, B Zhou, D Chu, Y Sun, L Meng. [Modality translation-based multimodal sentiment analysis under uncertain missing modalities]
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[36] Z Lin, B Liang, Y Long, Y Dang…. [Hierarchical Graph Contrastive Learning for Multimodal Sentiment Analysis]
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[37] A Zadeh, R Zellers, E Pincus, LP Morency. [Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos]
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[38] J Yang, Y Wang, R Yi, Y Zhu, A Rehman…. [Modal-Temporal Attention Graph for Unaligned Human Multimodal Language Sequences]
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[39] L Xiao, X Wu, W Wu, J Yang…. [MULTI-CHANNEL ATTENTIVE GRAPH CONVOLUTIONAL NETWORK WITH SENTIMENT FUSION FOR MULTIMODAL SENTIMENT ANALYSIS]
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[40] J Zheng, S Zhang, Z Wang, X Wang…. [Multi-Channel Weight-Sharing Autoencoder Based on Cascade Multi-Head Attention for Multimodal Emotion Recognition]
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[41] L Fang, G Liu, R Zhang. [MULTI-GRAINED MULTIMODAL INTERACTION NETWORK FOR SENTIMENT ANALYSIS]
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[42] S Poria, E Cambria, D Hazarika…. [Multi-level Multiple Attentions for Contextual Multimodal Sentiment Analysis]
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[43] MS Akhtar, DS Chauhan, D Ghosal, S Poria…. [Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis]
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[44] R Lin, H Hu. [Multimodal Contrastive Learning via Uni-Modal Coding and Cross-Modal Prediction for Multimodal Sentiment Analysis]
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[45] PP Liang, Z Liu, A Zadeh, LP Morency. [Multimodal Language Analysis with Recurrent Multistage Fusion]
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[46] Z Wu, Z Gong, J Koo, J Hirschberg. [Multimodal Multi-loss Fusion Network for Sentiment Analysis]
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[47] J Cheng, I Fostiropoulos, B Boehm…. [Multimodal Phased Transformer for Sentiment Analysis]
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[48] J Zheng, S Zhang, X Wang, Z Zeng. [Multimodal Representations Learning Based on Mutual Information Maximization and Minimization and Identity Embedding for Multimodal Sentiment Analysis]
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[49] Z Li, Q Guo, C Feng, L Deng, Q Zhang…. [Multimodal Sentiment Analysis Based on Interactive Transformer and Soft Mapping]
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[50] M Chen, S Wang, PP Liang, T Baltrušaitis…. [Multimodal Sentiment Analysis with Word-Level Fusion and Reinforcement Learning]
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[51] R Kaur, S Kautish. [Multimodal Sentiment Analysis: A Survey and Comparison]
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[52] A Gandhi, K Adhvaryu, S Poria, E Cambria, A Hussain. [A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions]
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[53] X Yang, S Feng, Y Zhang, D Wang. [Multimodal Sentiment Detection Based on Multi-channel Graph Neural Networks]
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[54] Huan Deng, Zhenguo Yang, Tianyong Hao, Qing Li, Wenyin Liu. [_Multimodal_Affective_Computing_With_Dense_Fusion_Transformer_for_Inter-and_Intra-Modality_Interactions]
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[55] MS Akhtar, DS Chauhan, D Ghosal, S Poria…. [NAACL19_Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis(1)]
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[56] F Wang, S Tian, L Yu, J Liu, J Wang, K Li…. [TEDT: Transformer-Based Encoding–Decoding Translation Network for Multimodal Sentiment Analysis]
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[57] H Luo, L Ji, Y Huang, B Wang, S Ji, T Li. [Improving Multimodal Sentiment Analysis via Multi-Scale Fusion of Locally Descriptors]
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[58] H Yang, X Gao, J Wu, T Gan, N Ding…. [Self-adaptive Context and Modal-interaction Modeling For Multimodal Emotion Recognition]
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[59] F Qian, J Han, Y He, T Zheng…. [Sentiment Knowledge Enhanced Self-supervised Learning for Multimodal Sentiment Analysis]
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[60] Y Wu, Y Zhao, H Yang, S Chen, B Qin, X Cao…. [Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR Errors]
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[61] S Lai, J Li, G Guo, X Hu, Y Li, Y Tan, Z Song…. [Shared and Private Information Learning in Multimodal Sentiment Analysis with Deep Modal Alignment and Self-supervised Multi-Task Learning]
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[62] C Zhu, M Chen, S Zhang, C Sun, H Liang, Y Liu…. [Sentiment Knowledge Enhanced Attention Fusion Network for multimodal sentiment analysis]
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[63] M Chen, X Li. [Sentimental Words Aware Fusion Network for Multimodal Sentiment Analysis]
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[64] Y Wei, S Yuan, R Yang, L Shen, Z Li…. [Tackling Modality Heterogeneity with Multi-View Calibration Network for Multimodal Sentiment Detection]
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[65] J Zeng, T Liu, J Zhou. [Tag-assisted Multimodal Sentiment Analysis under Uncertain]
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[66] J Yu, J Wang, R Xia, J Li. [Targeted Multimodal Sentiment Classifcation Based on Coarse-to-Fine Grained Image-Target Matching]
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[67] M Zhou, W Quan, Z Zhou, K Wang, T Wang…. [Text-oriented Cross Attention Network for Multimodal Sentiment Analysis]
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[68] C Huang, J Zhang, X Wu, Y Wang, M Li…. [Text-centered fusion network with crossmodal attention for multimodal sentiment analysis]
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[69] A Zadeh, M Chen, S Poria, E Cambria…. [Tensor Fusion Network for Multimodal Sentiment Analysis]
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[70] D Wang, X Guo, Y Tian, J Liu, LH He, X Luo. [A text enhanced transformer fusion network for multimodal sentiment analysis]
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[71] L Stappen, A Baird, L Schumann…. [The Multimodal Sentiment Analysis in Car Reviews (MuSe-CaR) Dataset: Collection, Insights and Improvements]
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[72] X Zhao, Y Chen, S Liu, X Zang, Y Xiang…. [A New Token Mixup Multimodal Data Augmentation for Multimodal Sentiment Analysis]
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[73] Y Li, W Weng, C Liu. [two-stage contrastive learning and feature hierarchical fusion network for multimodal sentiment analysis]
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[74] Y Zeng, S Mai, H Hu. [Modulating Unimodal and Cross-modal Dynamics for Multimodal Sentiment Analysis]
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[75] W Yu, H Xu, Z Yuan, J Wu. [_AAAI21_Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment Analysis]
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[76] Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, J. Zico Kolter, Louis-Philippe Morency, Ruslan Salakhutdinov. [_Multimodal Transformer for Unaligned Multimodal Language Sequences]
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[77] J Tang, K Li, X Jin, A Cichocki, Q Zhao…. [Hierarchical Learning for Multimodal Sentiment Analysis Using Coupled-Translation Fusion Network]
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[78] A Zadeh, YS Cao, S Hessner, PP Liang…. [A Multimodal Language Dataset for Spanish, Portuguese, German and French]
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[79] W Han, H Chen, S Poria. [_EMNLP21_Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis]
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[80] Z Yuan, W Li, H Xu, W Yu. [_MM21_Transformer-based Feature Reconstruction Network for Robust Multimodal Sentiment Analysis]
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[1] S Harata, T Sakuma, S Kato. [Audio-Visual Shared Emotion Representation for Robust Emotion Recognition on Modality Missing Using Hemi-hyperspherical Embedding and Latent Space Unification]
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[2] FA Rahman, G Lu. [A Contextualized Real-Time Multimodal Emotion Recognition for Conversational Agents using Graph Convolutional Networks in Reinforcement Learning]
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[3] W Zheng, J Yu, R Xia, S Wang. [A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party Conversations]
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[4] Y Zhang, J Wang, Y Liu, L Rong, Q Zheng, D Song…. [A Multitask learning model for multimodal sarcasm, sentiment and emotion recognition in conversations]
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[5] M Sharafi, M Yazdchi, R Rasti, F Nasimi. [A novel spatio-temporal convolutional neural framework for multimodal emotion recognition]
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[6] B Pan, K Hirota, Z Jia, Y Dai. [A review of multimodal emotion recognition from datasets, preprocessing, features, and fusion methods]
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[7] DS Chauhan, GV Singh, A Arora, A Ekbal…. [A Sentiment and Emotion aware Multimodal Multiparty Humor Recognition in Multilingual Conversational Setting]
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[8] X Li, J Song, Z Zhao, C Wang…. [A SUPERVISED INFORMATION ENHANCED MULTI-GRANULARITY CONTRASTIVE LEARNING FRAMEWORK FOR EEG BASED EMOTION RECOGNITION]
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[9] H Ma, J Wang, H Lin, B Zhang…. [A Transformer-based Model with Self-distillation for Multimodal Emotion Recognition in Conversations]
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[10] K Ali, CE Hughes. [A Unified Transformer-based Network for Multimodal Emotion Recognition]
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[11] J Vazquez-Rodriguez, G Lefebvre…. [ACCOMMODATING MISSING MODALITIES IN TIME-CONTINUOUS MULTIMODAL EMOTION RECOGNITION]
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[12] S Poria, D Hazarika, N Majumder, G Naik…. [A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations]
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[13] JA Miranda-Correa, MK Abadi…. [A Dataset for Affect, Personality and Mood Research on Individuals and Groups]
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[14] NK Devulapally, S Anand, SD Bhattacharjee…. [Adaptive Multimodal Analysis for Speaker Emotion Recognition in Group Conversations]
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[15] Fei Ma, Shao-Lun Huang, Lin Zhang. [An_Efficient_Approach_for_Audio-Visual_Emotion_Recognition_With_Missing_Labels_And_Missing_Modalities]
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[16] Hui Ma, Jian Wang, Hongfei Lin, Bo Zhang, Yijia Zhang, Bo Xu. [A_Transformer-Based_Model_With_Self-Distillation_for_Multimodal_Emotion_Recognition_in_Conversations]
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[17] A Jia, Y He, Y Zhang, S Uprety, D Song…. [A Multi-Modal Dataset for Human Desire Understanding]
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[18] X Zhang, Y Li. [A Cross-Modality Context Fusion and Semantic Refinement Network for Emotion Recognition in Conversation]
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[19] A Joshi, A Bhat, A Jain, A Singh…. [COntextualized GNN based Multimodal Emotion recognitioN]
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[20] Yahui Fu, Shogo Okada, Longbiao Wang, Lili Guo, Yaodong Song. [_Context-and_Knowledge-Aware_Graph_Convolutional_Network_for_Multimodal_Emotion_Recognition]
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[21] WY Choi, KY Song, CW Lee. [Convolutional Attention Networks for Multimodal Emotion Recognition from Speech and Text Data]
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[22] Y Wang, Y Li, P Bell, C Lai - researchgate.net. [Incongruity-Aware Dynamic Hierarchical Fusion for Multimodal Affect Recognition]
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[23] SAM Zaidi, S Latif, J Qadi. [Cross-Language Speech Emotion Recognition Using Multimodal Dual Attention Transformers]
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[24] Y Zhang, H Liu, D Wang, D Zhang, T Lou…. [Cross-modal credibility modelling for EEG-based multimodal emotion recognition]
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[25] L Xiao, X Wu, S Yang, J Xu, J Zhou, L He. [Cross-modal fine-grained alignment and fusion network for multimodal aspect-based sentiment analysis]
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[26] Y Li, Y Wang, Z Cui. [Decoupled Multimodal Distilling for Emotion Recognition]
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[27] F Zhang, XC Li, CP Lim, Q Hua, CR Dong, JH Zhai. [Deep Emotional Arousal Network for Multimodal Sentiment Analysis and Emotion Recognition]
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[28] AI Middya, B Nag, S Roy. [Deep learning based multimodal emotion recognition using model-level fusion of audio–visual modalities]
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[29] G Arora, M Sabharwal, P Kapila…. [Deep Residual Adaptive Neural Network Based Feature Extraction for Cognitive Computing with Multimodal Sentiment Sensing and Emotion Recognition Process]
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[30] Y Mao, Q Sun, G Liu, X Wang, W Gao, X Li…. [Exploring Multi-Modal Emotion Dynamics in Conversations]
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[31] Y Guo, C Tang, H Wu, B Chen. [EEG EMOTION RECOGNITION BASED ON DYNAMICAL GRAPH ATTENTION NETWORK]
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[32] GV Singh, M Firdaus, A Ekbal…. [A Multimodal Transformer for Identifying Emotions and Intents in Social Conversations]
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[33] K Ezzameli, H Mahersia. [Emotion recognition from unimodal to multimodal analysis: A review]
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[34] J Vazquez-Rodriguez, G Lefebvre…. [Emotion Recognition with Pre-Trained Transformers Using Multimodal Signals]
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[37] MM Islam, S Nooruddin, F Karray…. [A deep learning based model-level fusion approach]
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[38] H Zuo, R Liu, J Zhao, G Gao, H Li. [EXPLOITING MODALITY-INVARIANT FEATURE FOR ROBUST MULTIMODAL EMOTION RECOGNITION WITH MISSING MODALITIES]
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[39] Haolin Zuo, Rui Liu, Jinming Zhao, Guanglai Gao, Haizhou Li. [Exploiting_Modality-Invariant_Feature_for_Robust_Multimodal_Emotion_Recognition_with_Missing_Modalities]
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[40] Z Fang, A He, Q Yu, B Gao, W Ding, T Zhang…. [A novel multimodal emotion recognition approach integrating face, body and text]
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[41] X Yang, S Feng, D Wang, S Qi, W Wu, Y Zhang…. [Few-shot Joint Multimodal Aspect-Sentiment Analysis Based on Generative Multimodal Prompt]
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[42] YP Ruan, S Han, T Li, Y Wu. [FUSING MODALITY-SPECIFIC REPRESENTATIONS AND DECISIONS FOR MULTIMODAL EMOTION RECOGNITION]
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[43] M Jin, J Li. [Learning Deep Representations for Multimodal Emotion Recognition]
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[50] Z Tang, Q Xiao, X Zhou, Y Li, C Chen, K Li. [Learning discriminative multi-relation representations for multimodal sentiment analysis]
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[51] P Wang, S Zeng, J Chen, L Fan, M Chen, Y Wu…. [Leveraging Label Information for Multimodal Emotion Recognition]
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[52] V Chudasama, P Kar, A Gudmalwar…. [Multi-modal Fusion Network for Emotion Recognition in Conversation]
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[53] N Wang, H Cao, J Zhao, R Chen…. [Missing-Modality Robust Emotion Recognition Framework With Iterative Data Augmentation]
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[54] Y Zhang, A Jia, B Wang, P Zhang, D Zhao, P Li…. [A Multi-modal, Multi-task Interactive Graph Attention Network for Conversational Sentiment Analysis and Emotion Recognition]
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[55] M Ren, X Huang, J Liu, M Liu, X Li…. [Multimodal Adversarial Learning Network for Conversational Emotion Recognition]
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[56] M Firdaus, H Chauhan, A Ekbal…. [A Multimodal Multi-Label Emotion, Intensity and Sentiment Dialogue Dataset for Emotion Recognition and Sentiment Analysis in Conversations]
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[57] Z Lian, H Sun, L Sun, Z Wen, S Zhang, S Chen…. [Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition]
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[58] J Zhao, R Li, Q Jin. [Missing Modality Imagination Network for Emotion Recognition with Uncertain Missing Modalities]
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[61] T Shi, SL Huang. [An Attention-Based Correlation-Aware Multimodal Fusion Framework for Emotion Recognition in Conversations]
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[1] H Zhao, M Yang, X Bai, H Liu. [A Survey on Multimodal Aspect-Based Sentiment Analysis]
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[2] C Wang, Y Luo, C Meng, F Yuan. [An Adaptive Dual Graph Convolution Fusion Network for Aspect-Based Sentiment Analysis]
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[3] R Zhou, W Guo, X Liu, S Yu, Y Zhang…. [AoM Detecting Aspect-oriented Information for Multimodal]
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[6] Z Yu, J Wang, LC Yu, X Zhang. [Dual-Encoder Transformers with Cross-modal Alignment for Multimodal Aspect-based Sentiment Analysis]
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[7] Jianfei Yu, Jing Jiang, Rui Xia. [Entity-Sensitive_Attention_and_Fusion_Network_for_Entity-Level_Multimodal_Sentiment_Classification]
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[8] X Yang, S Feng, D Wang, S Qi, W Wu, Y Zhang…. [Few-shot Joint Multimodal Aspect-Sentiment Analysis Based on Generative Multimodal Prompt]
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[9] X Yang, S Feng, D Wang, S Qi, W Wu, Y Zhang…. [Few-shot joint multimodal aspect-sentiment analysis based on generative]
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[10] Jun Zhao, Fuping Yang. [Fusion_with_GCN_and_SE-ResNeXt_Network_for_Aspect_Based_Multimodal_Sentiment_Analysis]
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[12] Jianfei Yu, Kai Chen, Rui Xia. [Hierarchical_Interactive_Multimodal_Transformer_for_Aspect-Based_Multimodal_Sentiment_Analysis]
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[13] K Zhang, K Zhang, M Zhang, H Zhao, Q Liu…. [Incorporating Dynamic Semantics into Pre-Trained Language Model for Aspect-based Sentiment Analysis]
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[14] X Ju, D Zhang, R Xiao, J Li, S Li…. [Joint Multi-modal Aspect-Sentiment Analysis with Auxiliary Cross-modal Relation Detection]
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