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Deep Structure Inference Network for Facial Action Unit Recognition

arXiv 1803.05873 ↗First posted 15 Mar 2018cs.CVcited by 38

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Abstract (arXiv)

Facial expressions are combinations of basic components called Action Units (AU). Recognizing AUs is key for developing general facial expression analysis. In recent years, most efforts in automatic AU recognition have been dedicated to learning combinations of local features and to exploiting correlations between Action Units. In this paper, we propose a deep neural architecture that tackles both problems by combining learned local and global features in its initial stages and replicating a message passing algorithm between classes similar to a graphical model inference approach in later stages. We show that by training the model end-to-end with increased supervision we improve state-of-the-art by 5.3% and 8.2% performance on BP4D and DISFA datasets, respectively.

Key facts. Cited by 38 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Mar 2018.

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Citing papers per year: 2021: 5; 2022: 21; 2023: 4; 2024: 6; 2025: 1; 2026: 1.

38 papers.

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  1. 2022Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognitioncited by 82
  2. 2024Facial Affective Behavior Analysis with Instruction Tuningcited by 26
  3. 2024GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computingcited by 22
  4. 2022Facial Action Unit Detection and Intensity Estimation from Self-supervised Representationcited by 16
  5. 2023Weakly-Supervised Text-driven Contrastive Learning for Facial Behavior Understandingcited by 16
  6. 2021Graph-based Facial Affect Analysis: A Reviewcited by 14
  7. 2023Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit Detectioncited by 14
  8. 2023BigSmall: Efficient Multi-Task Learning for Disparate Spatial and Temporal Physiological Measurementscited by 13
  9. 2022Causal Intervention for Subject-Deconfounded Facial Action Unit Recognitioncited by 12
  10. 2022Multimodal Channel-Mixing: Channel and Spatial Masked AutoEncoder on Facial Action Unit Detectioncited by 11
  11. 2022Knowledge-augmented Deep Learning and Its Applications: A Surveycited by 10
  12. 2022Multi-label Transformer for Action Unit Detectioncited by 9
26 more
  1. 2021Meta Auxiliary Learning for Facial Action Unit Detectioncited by 6
  2. 2022Multi-Order Networks for Action Unit Detectioncited by 6
  3. 2022MGRR-Net: Multi-level Graph Relational Reasoning Network for Facial Action Units Detectioncited by 6
  4. 2024Facial Action Unit Detection by Adaptively Constraining Self-Attention and Causally Deconfounding Samplecited by 6
  5. 2022AFFDEX 2.0: A Real-Time Facial Expression Analysis Toolkitcited by 5
  6. 2022Multi-Modal Learning for AU Detection Based on Multi-Head Fused Transformerscited by 5
  7. 2022FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detectioncited by 5
  8. 2024Contrastive Learning of Person-independent Representations for Facial Action Unit Detectioncited by 5
  9. 2025OpenFace 3.0: A Lightweight Multitask System for Comprehensive Facial Behavior Analysiscited by 5
  10. 2022Your "Attention" Deserves Attention: A Self-Diversified Multi-Channel Attention for Facial Action Analysiscited by 4
  11. 2021Multi-Level Adaptive Region of Interest and Graph Learning for Facial Action Unit Recognitioncited by 3
  12. 2022Weakly Supervised Regional and Temporal Learning for Facial Action Unit Recognitioncited by 3
  13. 2026Hierarchical Vision-Language Interaction for Facial Action Unit Detectioncited by 3
  14. 2022Occlusion-Robust FAU Recognition by Mining Latent Space of Masked Autoencoderscited by 2
  15. 2024Learning Contrastive Feature Representations for Facial Action Unit Detectioncited by 2
  16. 2024Towards Unified Facial Action Unit Recognition Framework by Large Language Modelscited by 2
  17. 2021Self-Supervised Regional and Temporal Auxiliary Tasks for Facial Action Unit Recognitioncited by 1
  18. 2022Automatic Facial Paralysis Estimation with Facial Action Unitscited by 1
  19. 2022Knowledge-Spreader: Learning Facial Action Unit Dynamics with Extremely Limited Labelscited by 1
  20. 2022Facial Action Units Detection Aided by Global-Local Expression Embeddingcited by 1
  21. 2021Exploring Adversarial Learning for Deep Semi-Supervised Facial Action Unit Recognitioncited by 0
  22. 2022Cross-subject Action Unit Detection with Meta Learning and Transformer-based Relation Modelingcited by 0
  23. 2022Attention Based Relation Network for Facial Action Units Recognitioncited by 0
  24. 2022Global-to-local Expression-aware Embeddings for Facial Action Unit Detectioncited by 0
  25. 2022CorrLoss: Integrating Co-Occurrence Domain Knowledge for Affect Recognitioncited by 0
  26. 2023Fighting noise and imbalance in Action Unit detection problemscited by 0