mlsanityData to 7 Oct 2026

AU-aware graph convolutional network for Macro- and Micro-expression spotting

arXiv 2303.09114 ↗First posted 16 Mar 2023cs.CVcited by 9

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Abstract (arXiv)

Automatic Micro-Expression (ME) spotting in long videos is a crucial step in ME analysis but also a challenging task due to the short duration and low intensity of MEs. When solving this problem, previous works generally lack in considering the structures of human faces and the correspondence between expressions and relevant facial muscles. To address this issue for better performance of ME spotting, this paper seeks to extract finer spatial features by modeling the relationships between facial Regions of Interest (ROIs). Specifically, we propose a graph convolutional-based network, called Action-Unit-aWare Graph Convolutional Network (AUW-GCN). Furthermore, to inject prior information and to cope with the problem of small datasets, AU-related statistics are encoded into the network. Comprehensive experiments show that our results outperform baseline methods consistently and achieve new SOTA performance in two benchmark datasets,CAS(ME)^2 and SAMM-LV. Our code is available at https://github.com/xjtupanda/AUW-GCN.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 10 of its 36 references that are in the map. First posted on arXiv 16 Mar 2023.

Builds on

10 of 36 references.

References · 10

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  2. 2018BSN: Boundary Sensitive Network for Temporal Action Proposal Generationcited by 271
  3. 2018Style Aggregated Network for Facial Landmark Detectioncited by 60
  4. 2019Relation Modeling with Graph Convolutional Networks for Facial Action Unit Detectioncited by 25
  5. 2019SAMM Long Videos: A Spontaneous Facial Micro- and Macro-Expressions Datasetcited by 25
  6. 2020MER-GCN: Micro Expression Recognition Based on Relation Modeling with Graph Convolutional Networkcited by 21
  7. 2018A Survey of Automatic Facial Micro-expression Analysis: Databases, Methods and Challengescited by 16
  8. 20213D-CNN for Facial Micro- and Macro-expression Spotting on Long Video Sequences using Temporal Oriented Reference Framecited by 16
  9. 2021Shallow Optical Flow Three-Stream CNN for Macro- and Micro-Expression Spotting from Long Videoscited by 14
  10. 2016Objective Micro-Facial Movement Detection Using FACS-Based Regions and Baseline Evaluationcited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 5; 2026: 1.

9 papers.

  1. 2024Facial Expression Analysis and Its Potentials in IoT Systems: A Contemporary Surveycited by 5
  2. 2024Multi-Scale Spatio-Temporal Graph Convolutional Network for Facial Expression Spottingcited by 4
  3. 2024SpotFormer: Multi-Scale Spatio-Temporal Transformer for Facial Expression Spottingcited by 3
  4. 2025Causal-Ex: Causal Graph-based Micro and Macro Expression Spottingcited by 3
  5. 2025Infused Suppression Of Magnification Artefacts For Micro-AU Detectioncited by 3
  6. 2025MPFNet: A Multi-Prior Fusion Network with a Progressive Training Strategy for Micro-Expression Recognitioncited by 3
  7. 2026Evaluating and Correcting Human Annotation Bias in Dynamic Micro-Expression Recognitioncited by 2
  8. 2025End-to-End Facial Expression Detection in Long Videoscited by 0
  9. 2025Point-Supervised Facial Expression Spotting with Gaussian-Based Instance-Adaptive Intensity Modelingcited by 0