mlsanityData to 14 Oct 2026

Action Units Recognition Using Improved Pairwise Deep Architecture

arXiv 2107.03143 ↗First posted 7 Jul 2021cs.CVcited by 6

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Abstract (arXiv)

Facial Action Units (AUs) represent a set of facial muscular activities and various combinations of AUs can represent a wide range of emotions. AU recognition is often used in many applications, including marketing, healthcare, education, and so forth. Although a lot of studies have developed various methods to improve recognition accuracy, it still remains a major challenge for AU recognition. In the Affective Behavior Analysis in-the-wild (ABAW) 2020 competition, we proposed a new automatic Action Units (AUs) recognition method using a pairwise deep architecture to derive the Pseudo-Intensities of each AU and then convert them into predicted intensities. This year, we introduced a new technique to last year's framework to further reduce AU recognition errors due to temporary face occlusion such as hands on face or large face orientation. We obtained a score of 0.65 in the validation data set for this year's competition.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 13 of its 32 references that are in the map. First posted on arXiv 7 Jul 2021.

Builds on

13 of 32 references.

References · 13

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  2. 2016Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networkscited by 903
  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. 2020Analysing Affective Behavior in the First ABAW 2020 Competitioncited by 178
  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. 2021Analysing Affective Behavior in the second ABAW2 Competitioncited by 163
  9. 2019Face Behavior a la carte: Expressions, Affect and Action Units in a Single Networkcited by 155
  10. 2018Aff-Wild2: Extending the Aff-Wild Database for Affect Recognitioncited by 81
  11. 2017Action Unit Detection with Region Adaptation, Multi-labeling Learning and Optimal Temporal Fusingcited by 28
  12. 2018A Multi-Task Learning & Generation Framework: Valence-Arousal, Action Units & Primary Expressionscited by 25
1 more
  1. 2020Action Units Recognition by Pairwise Deep Architecturecited by 5

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Cited by year

Citing papers per year: 2022: 3; 2023: 1; 2024: 2.

6 papers.

  1. 2022ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challengescited by 156
  2. 2022ABAW: Learning from Synthetic Data & Multi-Task Learning Challengescited by 110
  3. 2023ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Emotional Reaction Intensity Estimation Challengescited by 110
  4. 2024The 6th Affective Behavior Analysis in-the-wild (ABAW) Competitioncited by 78
  5. 20247th ABAW Competition: Multi-Task Learning and Compound Expression Recognitioncited by 53
  6. 2022An Attention-based Method for Action Unit Detection at the 3rd ABAW Competitioncited by 4