mlsanityData to 7 Oct 2026

Technical Report for Valence-Arousal Estimation in ABAW2 Challenge

arXiv 2107.03891 ↗First posted 8 Jul 2021cs.CVcited by 6

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Abstract (arXiv)

In this work, we describe our method for tackling the valence-arousal estimation challenge from ABAW2 ICCV-2021 Competition. The competition organizers provide an in-the-wild Aff-Wild2 dataset for participants to analyze affective behavior in real-life settings. We use a two stream model to learn emotion features from appearance and action respectively. To solve data imbalanced problem, we apply label distribution smoothing (LDS) to re-weight labels. Our proposed method achieves Concordance Correlation Coefficient (CCC) of 0.591 and 0.617 for valence and arousal on the validation set of Aff-wild2 dataset.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 13 of its 18 references that are in the map. First posted on arXiv 8 Jul 2021.

Builds on

13 of 18 references.

References · 13

  1. 2017AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wildcited by 490
  2. 2019Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacecited by 222
  3. 2018Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyondcited by 216
  4. 2020Analysing Affective Behavior in the First ABAW 2020 Competitioncited by 178
  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. 2021Analysing Affective Behavior in the second ABAW2 Competitioncited by 163
  8. 2021Delving into Deep Imbalanced Regressioncited by 157
  9. 2019Face Behavior a la carte: Expressions, Affect and Action Units in a Single Networkcited by 155
  10. 2020Multitask Emotion Recognition with Incomplete Labelscited by 39
  11. 2018The OMG-Emotion Behavior Datasetcited by 25
  12. 2019MIMAMO Net: Integrating Micro- and Macro-motion for Video Emotion Recognitioncited by 17
1 more
  1. 2021Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognitioncited by 15

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Cited by year

Citing papers per year: 2022: 2; 2023: 1; 2024: 2; 2025: 1.

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. 2025MAVEN: Multi-modal Attention for Valence-Arousal Emotion Networkcited by 8