OpenFace 3.0: A Lightweight Multitask System for Comprehensive Facial Behavior Analysis

In recent years, there has been increasing interest in automatic facial behavior analysis systems from computing communities such as vision, multimodal interaction, robotics, and affective computing. Building upon the widespread utility of prior open-source facial analysis systems, we introduce OpenFace 3.0, an open-source toolkit capable of facial landmark detection, facial action unit detection, eye-gaze estimation, and facial emotion recognition. OpenFace 3.0 contributes a lightweight unified model for facial analysis, trained with a multi-task architecture across diverse populations, head poses, lighting conditions, video resolutions, and facial analysis tasks. By leveraging the benefits of parameter sharing through a unified model and training paradigm, OpenFACE 3.0 exhibits improvements in prediction performance, inference speed, and memory efficiency over similar toolkits and rivals state-of-theart models. Openface 3.0 can be installed and run with a single line of code and operate in real-time without specialized hardware. OpenFace 3.0 code for training models and running the system is freely available for research purposes and supports contributions from the community.

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Publication Details

Published
2025-05-26
DOI
https://doi.org/10.1109/fg61629.2025.11099277
Citations
6
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
12.71

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article

OpenFace 3.0: A Lightweight Multitask System for Comprehensive Facial Behavior Analysis

Leena Mathur, Paul Pu Liang, Jiewen Hu, Louis-Philippe Morency
6 citations
Emotion and Mood Recognition
12.71
article

OpenFace 3.0: A Lightweight Multitask System for Comprehensive Facial Behavior Analysis

Leena Mathur, Paul Pu Liang, Jiewen Hu, Louis-Philippe Morency
article en
6 citations

Abstract

In recent years, there has been increasing interest in automatic facial behavior analysis systems from computing communities such as vision, multimodal interaction, robotics, and affective computing. Building upon the widespread utility of prior open-source facial analysis systems, we introduce OpenFace 3.0, an open-source toolkit capable of facial landmark detection, facial action unit detection, eye-gaze estimation, and facial emotion recognition. OpenFace 3.0 contributes a lightweight unified model for facial analysis, trained with a multi-task architecture across diverse populations, head poses, lighting conditions, video resolutions, and facial analysis tasks. By leveraging the benefits of parameter sharing through a unified model and training paradigm, OpenFACE 3.0 exhibits improvements in prediction performance, inference speed, and memory efficiency over similar toolkits and rivals state-of-theart models. Openface 3.0 can be installed and run with a single line of code and operate in real-time without specialized hardware. OpenFace 3.0 code for training models and running the system is freely available for research purposes and supports contributions from the community.

Massachusetts Institute of Technology (US), Carnegie Mellon University (US)
HORIZON EUROPE Health
Gender equality
Openalex Percentile: Top 1%
Emotion and Mood Recognition
12.71
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OpenFace 3.0: A Lightweight Multitask System for Comprehensive Facial Behavior Analysis — Leena Mathur, Paul Pu Liang, et al. · (2025) | TGRS Research Map | TGRS