ArticleAffective science2023
Py-Feat: Python Facial Expression Analysis Toolbox.
Article in Affective science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
48 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of facial neuromuscular electrical stimulation (fNMES) in psychophysiological research: Practical recommendations based on a systematic review of the literature.Behavior research methods · 2024Guideline
- Trial
- From seeing to showing: towards a neuroscience of emotion production.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026Review
- Creating and validating photorealistic AI-generated facial expression stimuli for emotion research.Behavior research methods · 2026Article
- Adolescents and Adults Use Different Facial Movements and Vocal Cues to Express Emotions.Developmental science · 2026Article
- Decentralized Tele-Rehabilitation via Edge AI-Oracle Architecture for Spatiotemporal Pain Assessment.Sensors (Basel, Switzerland) · 2026Article
- Verbal and facial expression cues in emotional alignment.Scientific reports · 2026Article
- The Impact of Emotion Perception and Gaze Sharing on Collaborative Experience and Performance in Multiplayer Games.Journal of eye movement research · 2026Article
- Multivariate Timing and Granger Causality Analysis of Spontaneous Facial Mimicry in Response to Android Dynamic Facial Expressions.Sensors (Basel, Switzerland) · 2026Article
- Evaluating Open-Source Solutions for Computerized Inference of Infant Facial Affect.Developmental science · 2026Article
- Facial Expressions as a Nexus for Health Assessment.Bioengineering (Basel, Switzerland) · 2026Review
- LibreFace 2.0: A Generalizable Facial Expression Analysis Toolkit Leveraging Synthetic Data.Proceedings of the ... International Conference on Automatic Face and Gesture Recognition. IEEE International Conference on Automatic Face & Gesture Recognition · 2026Article
- Visually detectable facial mimicry in response to android facial expressions.Scientific reports · 2025Article
- Emoface: AI-assisted diagnostic model for differentiating major depressive disorder and bipolar disorder via facial biomarkers.Npj mental health research · 2025Article
- Comparing three algorithms of automated facial expression analysis in autistic children: different sensitivities but consistent proportions.Molecular autism · 2025Article
- duet: An R package for dyadic analysis of motion data generated by OpenPose.Behavior research methods · 2025Article
- Feature Analysis of Facial Color Information During Emotional Arousal in Japanese Older Adults Playing eSports.Sensors (Basel, Switzerland) · 2025Article
- Network models reveal high-dimensional social inferences in naturalistic settings beyond latent construct models.Communications psychology · 2025Article
- Monitoring of Early Skin Reactions by Optical Coherence Tomography and Dermatoscopy in Patients Receiving Radiation Therapy for Head and Neck Cancer.Advances in radiation oncology · 2025Article
- Beyond FACS: Data-driven Facial Expression Dictionaries, with Application to Predicting Autism.Proceedings of the ... International Conference on Automatic Face and Gesture Recognition. IEEE International Conference on Automatic Face & Gesture Recognition · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Studying facial expressions is a notoriously difficult endeavor. Recent advances in the field of affective computing have yielded impressive progress in automatically detecting facial expressions from pictures and videos. However, much of this work has yet to be widely disseminated in social science domains such as psychology. Current state-of-the-art models require considerable domain expertise that is not traditionally incorporated into social science training programs. Furthermore, there is a notable absence of user-friendly and open-source software that provides a comprehensive set of tools and functions that support facial expression research. In this paper, we introduce Py-Feat, an open-source Python toolbox that provides support for detecting, preprocessing, analyzing, and visualizing facial expression data. Py-Feat makes it easy for domain experts to disseminate and benchmark computer vision models and also for end users to quickly process, analyze, and visualize face expression data. We hope this platform will facilitate increased use of facial expression data in human behavior research. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-023-00191-4.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.