mlsanityData to 14 Oct 2026

Multi-Task Learning for Emotion Descriptors Estimation at the fourth ABAW Challenge

arXiv 2207.09716 ↗First posted 20 Jul 2022cs.CVcited by 3

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Abstract (arXiv)

Facial valence/arousal, expression and action unit are related tasks in facial affective analysis. However, the tasks only have limited performance in the wild due to the various collected conditions. The 4th competition on affective behavior analysis in the wild (ABAW) provided images with valence/arousal, expression and action unit labels. In this paper, we introduce multi-task learning framework to enhance the performance of three related tasks in the wild. Feature sharing and label fusion are used to utilize their relations. We conduct experiments on the provided training and validating data.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 9 of its 13 references that are in the map. First posted on arXiv 20 Jul 2022.

Builds on

9 of 13 references.

References · 9

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  4. 2019Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacecited by 222
  5. 2018Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyondcited by 216
  6. 2021Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Frameworkcited by 174
  7. 2021Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Studycited by 168
  8. 2022ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challengescited by 156
  9. 2018Photorealistic Facial Synthesis in the Dimensional Affect Spacecited by 33

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

3 papers.