mlsanityData to 7 Oct 2026

Facial Expression Classification using Fusion of Deep Neural Network in Video for the 3rd ABAW3 Competition

arXiv 2203.12899 ↗First posted 24 Mar 2022cs.CV eess.IVcited by 5

Not on the map. Why?

Abstract (arXiv)

For computers to recognize human emotions, expression classification is an equally important problem in the human-computer interaction area. In the 3rd Affective Behavior Analysis In-The-Wild competition, the task of expression classification includes eight classes with six basic expressions of human faces from videos. In this paper, we employ a transformer mechanism to encode the robust representation from the backbone. Fusion of the robust representations plays an important role in the expression classification task. Our approach achieves 30.35% and 28.60% for the F1 score on the validation set and the test set, respectively. This result shows the effectiveness of the proposed architecture based on the Aff-Wild2 dataset.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 20 of its 29 references that are in the map. First posted on arXiv 24 Mar 2022.

Builds on

20 of 29 references.

References · 20

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  5. 2020Designing Network Design Spacescited by 954
  6. 2017Focal Loss for Dense Object Detectioncited by 749
  7. 2019Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacecited by 222
  8. 2018Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyondcited by 216
  9. 2020Analysing Affective Behavior in the First ABAW 2020 Competitioncited by 178
  10. 2021Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Frameworkcited by 174
  11. 2021Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Studycited by 168
  12. 2021Analysing Affective Behavior in the second ABAW2 Competitioncited by 163
8 more
  1. 2022ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challengescited by 156
  2. 2019Face Behavior a la carte: Expressions, Affect and Action Units in a Single Networkcited by 155
  3. 2022Transformer-based Multimodal Information Fusion for Facial Expression Analysiscited by 49
  4. 2021A Multi-modal and Multi-task Learning Method for Action Unit and Expression Recognitioncited by 24
  5. 2021Iterative Distillation for Better Uncertainty Estimates in Multitask Emotion Recognitioncited by 20
  6. 2021A Multi-task Mean Teacher for Semi-supervised Facial Affective Behavior Analysiscited by 19
  7. 2020Affect Expression Behaviour Analysis in the Wild using Spatio-Channel Attention and Complementary Context Informationcited by 13
  8. 2021Emotion Recognition with Incomplete Labels Using Modified Multi-task Learning Techniquecited by 10

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 2; 2024: 2.

5 papers.

  1. 2022ABAW: Learning from Synthetic Data & Multi-Task Learning Challengescited by 110
  2. 2024The 6th Affective Behavior Analysis in-the-wild (ABAW) Competitioncited by 78
  3. 2023Multi-modal Facial Affective Analysis based on Masked Autoencodercited by 23
  4. 2023Multimodal Feature Extraction and Fusion for Emotional Reaction Intensity Estimation and Expression Classification in Videos with Transformerscited by 5
  5. 2024Multimodal Fusion with Pre-Trained Model Features in Affective Behaviour Analysis In-the-wildcited by 1