The DOI matches its Crossref record, with a small difference in title or year.
Facial Action Coding System
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“FOMM learns dense optical low to support complex motions with fewer artifacts, whereas ICface and FSGAN only use sparse action units [13] or facial landmarks to learn the expression and pose, which tend to produce motion artifacts.”
From DEEPFAKER: A Unified Evaluation Platform for Facial Deepfake and Detection Models (2024) · cites this paper as [13]
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Jennings, P. A., & Greenberg, M. T. (2009) · Review of Educational Research · doi:10.3102/0034654308325693 · Cited by 3,686
Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
Zhao, G., & Pietikainen, M. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1110 · Cited by 2,846
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.52 · Cited by 2,797
Autonomic nervous system activity distinguishes among emotions
Ekman, P., Levenson, R. W., & Friesen, W. V. (1983) · Science · doi:10.1126/science.6612338 · Cited by 2,692
Self-citationComprehensive database for facial expression analysis
Takeo Kanade, A., Cohn, J. F., & Tian, Y. (2002) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.2000.840611 · Cited by 2,644
Metadata
- Authors
- Ekman, P., & Friesen, W. V.
- Venue
- PsycTESTS Dataset
- Published
- 1978
- OpenAlex
- W1588539311
- Cited by
- 6,019
- References
- 0
- Citations by year
- 2026: 288 · 2025: 447 · 2024: 367 · 2023: 379 · 2022: 314 · 2021: 204 · 2020: 218 · 2019: 195 · 2018: 227 · 2017: 199 · 2016: 244 · 2015: 233 · 2014: 214 · 2013: 208 · 2012: 174
- Type
- dataset
- Language
- en
- Open access
- closed
- Locations
- PsycTESTS Dataset (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- facial expressions, facial action units, emotion recognition, facial motion
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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