# Affective Expression Analysis in-the-wild using Multi-Task Temporal Statistical Deep Learning Model

arXiv: https://arxiv.org/abs/2002.09120 · HTML: https://mlsanity.com/paper/2002.09120/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Feb 2020.

## Built on by (most cited first, 8 of 8)

- [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)
- [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)
- [Continuous-Time Audiovisual Fusion with Recurrence vs. Attention for In-The-Wild Affect Recognition](https://mlsanity.com/paper/2203.13285/) (2022)
- [Critically examining the Domain Generalizability of Facial Expression Recognition models](https://mlsanity.com/paper/2106.15453/) (2021)

## Abstract (arXiv)

Affective behavior analysis plays an important role in human-computer interaction, customer marketing, health monitoring. ABAW Challenge and Aff-Wild2 dataset raise the new challenge for classifying basic emotions and regression valence-arousal value under in-the-wild environments. In this paper, we present an affective expression analysis model that deals with the above challenges. Our approach includes STAT and Temporal Module for fine-tuning again face feature model. We experimented on Aff-Wild2 dataset, a large-scale dataset for ABAW Challenge with the annotations for both the categorical and valence-arousal emotion. We achieved the expression score 0.543 and valence-arousal score 0.534 on the validation set.