# Multi-modal Multi-label Facial Action Unit Detection with Transformer

arXiv: https://arxiv.org/abs/2203.13301 · HTML: https://mlsanity.com/paper/2203.13301/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 16 references that are in the map.
- First posted on arXiv 24 Mar 2022.

## Builds on (most cited first, 12 of 12)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace](https://mlsanity.com/paper/1910.04855/) (2019)
- [Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond](https://mlsanity.com/paper/1804.10938/) (2018)
- [Analysing Affective Behavior in the First ABAW 2020 Competition](https://mlsanity.com/paper/2001.11409/) (2020)
- [Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework](https://mlsanity.com/paper/2103.15792/) (2021)
- [Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study](https://mlsanity.com/paper/2105.03790/) (2021)
- [Analysing Affective Behavior in the second ABAW2 Competition](https://mlsanity.com/paper/2106.15318/) (2021)
- [ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challenges](https://mlsanity.com/paper/2202.10659/) (2022)
- [Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network](https://mlsanity.com/paper/1910.11111/) (2019)
- [Two-Stream Aural-Visual Affect Analysis in the Wild](https://mlsanity.com/paper/2002.03399/) (2020)
- [A Multi-modal and Multi-task Learning Method for Action Unit and Expression Recognition](https://mlsanity.com/paper/2107.04187/) (2021)

## Built on by (most cited first, 10 of 10)

- [ABAW: Learning from Synthetic Data & Multi-Task Learning Challenges](https://mlsanity.com/paper/2207.01138/) (2022)
- [ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Emotional Reaction Intensity Estimation Challenges](https://mlsanity.com/paper/2303.01498/) (2023)
- [The 6th Affective Behavior Analysis in-the-wild (ABAW) Competition](https://mlsanity.com/paper/2402.19344/) (2024)
- [7th ABAW Competition: Multi-Task Learning and Compound Expression Recognition](https://mlsanity.com/paper/2407.03835/) (2024)
- [Facial Affect Recognition based on Transformer Encoder and Audiovisual Fusion for the ABAW5 Challenge](https://mlsanity.com/paper/2303.09158/) (2023)
- [Local Region Perception and Relationship Learning Combined with Feature Fusion for Facial Action Unit Detection](https://mlsanity.com/paper/2303.08545/) (2023)
- [Vision Transformer for Action Units Detection](https://mlsanity.com/paper/2303.09917/) (2023)
- [Spatial-temporal Transformer for Affective Behavior Analysis](https://mlsanity.com/paper/2303.10561/) (2023)
- [Facial Affect Recognition based on Multi Architecture Encoder and Feature Fusion for the ABAW7 Challenge](https://mlsanity.com/paper/2407.12258/) (2024)
- [Compound Expression Recognition via Multi Model Ensemble for the ABAW7 Challenge](https://mlsanity.com/paper/2407.12257/) (2024)

## Abstract (arXiv)

Facial Action Coding System is an important approach of facial expression analysis.This paper describes our submission to the third Affective Behavior Analysis (ABAW) 2022 competition. We proposed a transfomer based model to detect facial action unit (FAU) in video. To be specific, we firstly trained a multi-modal model to extract both audio and visual feature. After that, we proposed a action units correlation module to learn relationships between each action unit labels and refine action unit detection result. Experimental results on validation dataset shows that our method achieves better performance than baseline model, which verifies that the effectiveness of proposed network.