mlsanityData to 14 Oct 2026

FEAFA+: An Extended Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation

arXiv 2111.02751 ↗First posted 4 Nov 2021cs.CV cs.GR cs.LGcited by 7

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Abstract (arXiv)

Nearly all existing Facial Action Coding System-based datasets that include facial action unit (AU) intensity information annotate the intensity values hierarchically using A--E levels. However, facial expressions change continuously and shift smoothly from one state to another. Therefore, it is more effective to regress the intensity value of local facial AUs to represent whole facial expression changes, particularly in the fields of expression transfer and facial animation. We introduce an extension of FEAFA in combination with the relabeled DISFA database, which is available at https://www.iiplab.net/feafa+/ now. Extended FEAFA (FEAFA+) includes 150 video sequences from FEAFA and DISFA, with a total of 230,184 frames being manually annotated on floating-point intensity value of 24 redefined AUs using the Expression Quantitative Tool. We also list crude numerical results for posed and spontaneous subsets and provide a baseline comparison for the AU intensity regression task.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 8 of its 36 references that are in the map. First posted on arXiv 4 Nov 2021.

Builds on

8 of 36 references.

References · 8

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  3. 2014Going Deeper with Convolutionscited by 4,241
  4. 2019Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacecited by 222
  5. 2018Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyondcited by 216
  6. 2018AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detectioncited by 14
  7. 2020RAF-AU Database: In-the-Wild Facial Expressions with Subjective Emotion Judgement and Objective AU Annotationscited by 11
  8. 2019FEAFA: A Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animationcited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 4; 2025: 1; 2026: 1.

7 papers.

  1. 2024ExpLLM: Towards Chain of Thought for Facial Expression Recognitioncited by 15
  2. 2024AffectNet+: A Database for Enhancing Facial Expression Recognition with Soft-Labelscited by 9
  3. 2023NeutrEx: A 3D Quality Component Measure on Facial Expression Neutralitycited by 4
  4. 2025AU-Blendshape for Fine-grained Stylized 3D Facial Expression Manipulationcited by 3
  5. 2024Towards Unified Facial Action Unit Recognition Framework by Large Language Modelscited by 2
  6. 2026AUHead: Realistic Emotional Talking Head Generation via Action Units Controlcited by 1
  7. 2024Efficient Expression Neutrality Estimation with Application to Face Recognition Utility Predictioncited by 0