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Feature-Based Dual Visual Feature Extraction Model for Compound Multimodal Emotion Recognition

arXiv 2503.17453 ↗First posted 21 Mar 2025cs.CVcited by 0

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Abstract (arXiv)

This article presents our results for the eighth Affective Behavior Analysis in-the-wild (ABAW) competition.Multimodal emotion recognition (ER) has important applications in affective computing and human-computer interaction. However, in the real world, compound emotion recognition faces greater issues of uncertainty and modal conflicts. For the Compound Expression (CE) Recognition Challenge,this paper proposes a multimodal emotion recognition method that fuses the features of Vision Transformer (ViT) and Residual Network (ResNet). We conducted experiments on the C-EXPR-DB and MELD datasets. The results show that in scenarios with complex visual and audio cues (such as C-EXPR-DB), the model that fuses the features of ViT and ResNet exhibits superior performance.Our code are avalible on https://github.com/MyGitHub-ax/8th_ABAW

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References · 13

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2018An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modelingcited by 1,476
  4. 2016CNN Architectures for Large-Scale Audio Classificationcited by 704
  5. 2018MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversationscited by 643
  6. 2016MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognitioncited by 624
  7. 2020Visual Transformers: Token-based Image Representation and Processing for Computer Visioncited by 334
  8. 2024Distribution Matching for Multi-Task Learning of Classification Tasks: a Large-Scale Study on Faces & Beyondcited by 60
  9. 20247th ABAW Competition: Multi-Task Learning and Compound Expression Recognitioncited by 53
  10. 2022MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Modelcited by 41
  11. 2024Distilling Privileged Multimodal Information for Expression Recognition using Optimal Transportcited by 15
  12. 2024Guided Interpretable Facial Expression Recognition via Spatial Action Unit Cuescited by 11
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  1. 2024Textualized and Feature-based Models for Compound Multimodal Emotion Recognition in the Wildcited by 9

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