mlsanityData to 7 Oct 2026

GraphAU-Pain: Graph-based Action Unit Representation for Pain Intensity Estimation

arXiv 2505.19802 ↗First posted 26 May 2025cs.LG cs.CVcited by 0

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Abstract (arXiv)

Understanding pain-related facial behaviors is essential for digital healthcare in terms of effective monitoring, assisted diagnostics, and treatment planning, particularly for patients unable to communicate verbally. Existing data-driven methods of detecting pain from facial expressions are limited due to interpretability and severity quantification. To this end, we propose GraphAU-Pain, leveraging a graph-based framework to model facial Action Units (AUs) and their interrelationships for pain intensity estimation. AUs are represented as graph nodes, with co-occurrence relationships as edges, enabling a more expressive depiction of pain-related facial behaviors. By utilizing a relational graph neural network, our framework offers improved interpretability and significant performance gains. Experiments conducted on the publicly available UNBC dataset demonstrate the effectiveness of the GraphAU-Pain, achieving an F1-score of 66.21% and accuracy of 87.61% in pain intensity estimation.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 52 references that are in the map. First posted on arXiv 26 May 2025.

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References · 12

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2021Video Swin Transformercited by 1,090
  3. 2020Graph Neural Networks in Recommender Systems: A Surveycited by 493
  4. 2022Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognitioncited by 81
  5. 2018Facial Action Unit Detection Using Attention and Relation Learningcited by 46
  6. 2024KG4Diagnosis: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Medical Diagnosiscited by 26
  7. 2021Graph-based Facial Affect Analysis: A Reviewcited by 14
  8. 2016Recurrent Convolutional Neural Network Regression for Continuous Pain Intensity Estimation in Videocited by 12
  9. 2022Uncertain Facial Expression Recognition via Multi-task Assisted Correctioncited by 10
  10. 2022Uncertain Label Correction via Auxiliary Action Unit Graphs for Facial Expression Recognitioncited by 8
  11. 2018Automated Pain Detection from Facial Expressions using FACS: A Reviewcited by 6
  12. 2017Learning Pain from Action Unit Combinations: A Weakly Supervised Approach via Multiple Instance Learningcited by 3

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