MMSP-P4: Multimodal Emotion/Sentiment Analysis
Wed, 17 Apr, 13:10 - 15:10 (UTC +9)
Location: Poster Zone 5B
Session Type: Poster
Session Chair: Zhaojun Yang, Meta, US
Track: Multimedia Signal Processing
Click the to view the manuscript on IEEE Xplore Open Preview
 

MMSP-P4.1: ATTA-NET: ATTENTION AGGREGATION NETWORK FOR AUDIO-VISUAL EMOTION RECOGNITION

Ruijia Fan, Hong Liu, Peking University, China; Yidi Li, Taiyuan University of Technology, China; Peini Guo, Guoquan Wang, Ti Wang, Peking University, China
 

MMSP-P4.2: Fusing Modality-Specific Representations and Decisions for Multimodal Emotion Recognition

Yu-Ping Ruan, Shoukang Han, Taihao Li, Yanfeng Wu, Zhejiang Lab, China
 

MMSP-P4.4: CLIP-MSA: INCORPORATING INTER-MODAL DYNAMICS AND COMMON KNOWLEDGE TO MULTIMODAL SENTIMENT ANALYSIS WITH CLIP

Qi Huang, Pingting Cai, Tanyue Nie, Jinshan Zeng, Jiangxi Normal University, China
 

MMSP-P4.5: GUIDED CIRCULAR DECOMPOSITION AND CROSS-MODAL RECOMBINATION FOR MULTIMODAL SENTIMENT ANALYSIS

Haijian Liang, Weicheng Xie, Xilin He, Shenzhen University, China; Siyang Song, University of Leicester, United Kingdom of Great Britain and Northern Ireland; Linlin Shen, Shenzhen University, China
 

MMSP-P4.6: A NOVEL MULTIMODAL SENTIMENT ANALYSIS MODEL BASED ON GATED FUSION AND MULTI-TASK LEARNING

Xin Sun, Xiangyu Ren, Xiaohao Xie, Beijing Institute of Technology, China
 

MMSP-P4.7: Modality-dependent sentiments exploring for multi-modal sentiment classification

Jingzhe Li, Chengji Wang, Central China Normal University, China; Zhiming Luo, Xiamen University, China; Yuxian Wu, Xingpeng Jiang, Central China Normal University, China
 

MMSP-P4.8: EMOTION-ALIGNED CONTRASTIVE LEARNING BETWEEN IMAGES AND MUSIC

Shanti Stewart, Kleanthis Avramidis, Tiantian Feng, Shrikanth Narayanan, University of Southern California, United States of America
 

MMSP-P4.10: INTER-MODALITY AND INTRA-SAMPLE ALIGNMENT FOR MULTI-MODAL EMOTION RECOGNITION

Yusong Wang, Dongyuan Li, Jialun Shen, Tokyo Institute of Technology, China
 

MMSP-P4.11: MDAVIF: A MULTI-DOMAIN ACOUSTICAL-VISUAL INFORMATION FUSION MODEL FOR DEPRESSION RECOGNITION FROM VLOG DATA

Tianfei Ling, Deyuan Chen, Baobin Li, University of Chinese Academy of Sciences, China