mlsanityData to 7 Oct 2026

AFFDEX 2.0: A Real-Time Facial Expression Analysis Toolkit

arXiv 2202.12059 ↗First posted 24 Feb 2022cs.CVcited by 5

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Abstract (arXiv)

In this paper we introduce AFFDEX 2.0 - a toolkit for analyzing facial expressions in the wild, that is, it is intended for users aiming to; a) estimate the 3D head pose, b) detect facial Action Units (AUs), c) recognize basic emotions and 2 new emotional states (sentimentality and confusion), and d) detect high-level expressive metrics like blink and attention. AFFDEX 2.0 models are mainly based on Deep Learning, and are trained using a large-scale naturalistic dataset consisting of thousands of participants from different demographic groups. AFFDEX 2.0 is an enhanced version of our previous toolkit [1], that is capable of tracking efficiently faces at more challenging conditions, detecting more accurately facial expressions, and recognizing new emotional states (sentimentality and confusion). AFFDEX 2.0 can process multiple faces in real time, and is working across the Windows and Linux platforms.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 11 of its 49 references that are in the map. First posted on arXiv 24 Feb 2022.

Builds on

11 of 49 references.

References · 11

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  2. 2018Deep Facial Expression Recognition: A Surveycited by 269
  3. 2022ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challengescited by 156
  4. 2018Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignmentcited by 55
  5. 2019Semantic Relationships Guided Representation Learning for Facial Action Unit Recognitioncited by 53
  6. 2018Facial Action Unit Detection Using Attention and Relation Learningcited by 46
  7. 2018Deep Structure Inference Network for Facial Action Unit Recognitioncited by 38
  8. 2018SchiNet: Automatic Estimation of Symptoms of Schizophrenia from Facial Behaviour Analysiscited by 16
  9. 2016Automatic Detection of ADHD and ASD from Expressive Behaviour in RGBD Datacited by 6
  10. 2021Which CNNs and Training Settings to Choose for Action Unit Detection? A Study Based on a Large-Scale Datasetcited by 3
  11. 2021Choose Settings Carefully: Comparing Action Unit detection at Different Settings Using a Large-Scale Datasetcited by 2

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 1; 2025: 3.

5 papers.

  1. 2023LibreFace: An Open-Source Toolkit for Deep Facial Expression Analysiscited by 18
  2. 2024Behaviour4All: in-the-wild Facial Behaviour Analysis Toolkitcited by 16
  3. 2025OpenFace 3.0: A Lightweight Multitask System for Comprehensive Facial Behavior Analysiscited by 5
  4. 2025Monitoring Viewer Attention During Online Adscited by 0
  5. 2025PainNet: Statistical Relation Network with Episode-Based Training for Pain Estimationcited by 0