mlsanityData to 14 Oct 2026

Spatial and Temporal Networks for Facial Expression Recognition in the Wild Videos

arXiv 2107.05160 ↗First posted 12 Jul 2021cs.CV eess.IVcited by 5

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Abstract (arXiv)

The paper describes our proposed methodology for the seven basic expression classification track of Affective Behavior Analysis in-the-wild (ABAW) Competition 2021. In this task, facial expression recognition (FER) methods aim to classify the correct expression category from a diverse background, but there are several challenges. First, to adapt the model to in-the-wild scenarios, we use the knowledge from pre-trained large-scale face recognition data. Second, we propose an ensemble model with a convolution neural network (CNN), a CNN-recurrent neural network (CNN-RNN), and a CNN-Transformer (CNN-Transformer), to incorporate both spatial and temporal information. Our ensemble model achieved F1 as 0.4133, accuracy as 0.6216 and final metric as 0.4821 on the validation set.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 13 of its 16 references that are in the map. First posted on arXiv 12 Jul 2021.

Builds on

13 of 16 references.

References · 13

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,057
  4. 2017VGGFace2: A dataset for recognising faces across pose and agecited by 914
  5. 2019Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacecited by 222
  6. 2018Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyondcited by 216
  7. 2020Analysing Affective Behavior in the First ABAW 2020 Competitioncited by 178
  8. 2021Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Frameworkcited by 174
  9. 2021Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Studycited by 168
  10. 2021Analysing Affective Behavior in the second ABAW2 Competitioncited by 163
  11. 2020Suppressing Uncertainties for Large-Scale Facial Expression Recognitioncited by 157
  12. 2019Face Behavior a la carte: Expressions, Affect and Action Units in a Single Networkcited by 155
1 more
  1. 2019Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognitioncited by 127

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Cited by year

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

5 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