# Prior Aided Streaming Network for Multi-task Affective Recognitionat the 2nd ABAW2 Competition

arXiv: https://arxiv.org/abs/2107.03708 · HTML: https://mlsanity.com/paper/2107.03708/

## Key facts

- Cited by 18 papers in the map (data through 7 Oct 2026).
- Builds on 16 of its 31 references that are in the map.
- First posted on arXiv 8 Jul 2021.

## Builds on (most cited first, 16 of 16)

- [AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild](https://mlsanity.com/paper/1708.03985/) (2017)
- [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)
- [Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network](https://mlsanity.com/paper/1910.11111/) (2019)
- [DFEW: A Large-Scale Database for Recognizing Dynamic Facial Expressions in the Wild](https://mlsanity.com/paper/2008.05924/) (2020)
- [Two-Stream Aural-Visual Affect Analysis in the Wild](https://mlsanity.com/paper/2002.03399/) (2020)
- [A Compact Embedding for Facial Expression Similarity](https://mlsanity.com/paper/1811.11283/) (2018)
- [Multitask Emotion Recognition with Incomplete Labels](https://mlsanity.com/paper/2002.03557/) (2020)
- [Facial Expression Retargeting from Human to Avatar Made Easy](https://mlsanity.com/paper/2008.05110/) (2020)
- [Affect Expression Behaviour Analysis in the Wild using Spatio-Channel Attention and Complementary Context Information](https://mlsanity.com/paper/2009.14440/) (2020)
- [Joint Binary Neural Network for Multi-label Learning with Applications to Emotion Classification](https://mlsanity.com/paper/1802.00891/) (2018)
- [Action Units Recognition by Pairwise Deep Architecture](https://mlsanity.com/paper/2010.00288/) (2020)

## Built on by (most cited first, 18 of 18)

- [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)
- [Vision Transformer with Attentive Pooling for Robust Facial Expression Recognition](https://mlsanity.com/paper/2212.05463/) (2022)
- [A Multi-task Mean Teacher for Semi-supervised Facial Affective Behavior Analysis](https://mlsanity.com/paper/2107.04225/) (2021)
- [Coarse-to-Fine Cascaded Networks with Smooth Predicting for Video Facial Expression Recognition](https://mlsanity.com/paper/2203.13052/) (2022)
- [Frame-level Prediction of Facial Expressions, Valence, Arousal and Action Units for Mobile Devices](https://mlsanity.com/paper/2203.13436/) (2022)
- [Norface: Improving Facial Expression Analysis by Identity Normalization](https://mlsanity.com/paper/2407.15617/) (2024)
- [Multiple Emotion Descriptors Estimation at the ABAW3 Challenge](https://mlsanity.com/paper/2203.12845/) (2022)
- [An Ensemble Approach for Facial Expression Analysis in Video](https://mlsanity.com/paper/2203.12891/) (2022)
- [Spatio-Temporal AU Relational Graph Representation Learning For Facial Action Units Detection](https://mlsanity.com/paper/2303.10644/) (2023)
- [Multitask Emotion Recognition Model with Knowledge Distillation and Task Discriminator](https://mlsanity.com/paper/2203.13072/) (2022)
- [Exploring Expression-related Self-supervised Learning for Affective Behaviour Analysis](https://mlsanity.com/paper/2303.10511/) (2023)
- [Computer Vision Estimation of Emotion Reaction Intensity in the Wild](https://mlsanity.com/paper/2303.10741/) (2023)
- [ARPGNet: Appearance- and Relation-aware Parallel Graph Attention Fusion Network for Facial Expression Recognition](https://mlsanity.com/paper/2511.22188/) (2025)
- [Consensual Collaborative Training And Knowledge Distillation Based Facial Expression Recognition Under Noisy Annotations](https://mlsanity.com/paper/2107.04746/) (2021)

## Abstract (arXiv)

Automatic affective recognition has been an important research topic in human computer interaction (HCI) area. With recent development of deep learning techniques and large scale in-the-wild annotated datasets, the facial emotion analysis is now aimed at challenges in the real world settings. In this paper, we introduce our submission to the 2nd Affective Behavior Analysis in-the-wild (ABAW2) Competition. In dealing with different emotion representations, including Categorical Emotions (CE), Action Units (AU), and Valence Arousal (VA), we propose a multi-task streaming network by a heuristic that the three representations are intrinsically associated with each other. Besides, we leverage an advanced facial expression embedding as prior knowledge, which is capable of capturing identity-invariant expression features while preserving the expression similarities, to aid the down-streaming recognition tasks. The extensive quantitative evaluations as well as ablation studies on the Aff-Wild2 dataset prove the effectiveness of our proposed prior aided streaming network approach.