mlsanityData to 14 Oct 2026

An Ensemble Approach for Multiple Emotion Descriptors Estimation Using Multi-task Learning

arXiv 2207.10878 ↗First posted 22 Jul 2022cs.CV cs.AIcited by 3

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Abstract (arXiv)

This paper illustrates our submission method to the fourth Affective Behavior Analysis in-the-Wild (ABAW) Competition. The method is used for the Multi-Task Learning Challenge. Instead of using only face information, we employ full information from a provided dataset containing face and the context around the face. We utilized the InceptionNet V3 model to extract deep features then we applied the attention mechanism to refine the features. After that, we put those features into the transformer block and multi-layer perceptron networks to get the final multiple kinds of emotion. Our model predicts arousal and valence, classifies the emotional expression and estimates the action units simultaneously. The proposed system achieves the performance of 0.917 on the MTL Challenge validation dataset.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 18 of its 31 references that are in the map. First posted on arXiv 22 Jul 2022.

Builds on

18 of 31 references.

References · 18

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  2. 2015Learning Deep Features for Discriminative Localizationcited by 2,436
  3. 2019Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacecited by 222
  4. 2018Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyondcited by 216
  5. 2021Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Frameworkcited by 174
  6. 2021Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Studycited by 168
  7. 2022ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challengescited by 156
  8. 2022ABAW: Learning from Synthetic Data & Multi-Task Learning Challengescited by 110
  9. 2018Aff-Wild2: Extending the Aff-Wild Database for Affect Recognitioncited by 81
  10. 2020Two-Stream Aural-Visual Affect Analysis in the Wildcited by 51
  11. 2020Multitask Emotion Recognition with Incomplete Labelscited by 39
  12. 2018Photorealistic Facial Synthesis in the Dimensional Affect Spacecited by 33
6 more
  1. 2021Iterative Distillation for Better Uncertainty Estimates in Multitask Emotion Recognitioncited by 21
  2. 2017Facial Expression Recognition Using Enhanced Deep 3D Convolutional Neural Networkscited by 17
  3. 2016Track and Transfer: Watching Videos to Simulate Strong Human Supervision for Weakly-Supervised Object Detectioncited by 9
  4. 2022Multiple Emotion Descriptors Estimation at the ABAW3 Challengecited by 9
  5. 2020A Multi-term and Multi-task Analyzing Framework for Affective Analysis in-the-wildcited by 8
  6. 2021Multi-modal Affect Analysis using standardized data within subjects in the Wildcited by 4

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Cited by year

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

3 papers.

  1. 2023ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Emotional Reaction Intensity Estimation Challengescited by 110
  2. 2024The 6th Affective Behavior Analysis in-the-wild (ABAW) Competitioncited by 78
  3. 20247th ABAW Competition: Multi-Task Learning and Compound Expression Recognitioncited by 53