mlsanityData to 14 Oct 2026

HSEmotion Team at the 6th ABAW Competition: Facial Expressions, Valence-Arousal and Emotion Intensity Prediction

arXiv 2403.11590 ↗First posted 18 Mar 2024cs.CVcited by 8

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Abstract (arXiv)

This article presents our results for the sixth Affective Behavior Analysis in-the-wild (ABAW) competition. To improve the trustworthiness of facial analysis, we study the possibility of using pre-trained deep models that extract reliable emotional features without the need to fine-tune the neural networks for a downstream task. In particular, we introduce several lightweight models based on MobileViT, MobileFaceNet, EfficientNet, and DDAMFN architectures trained in multi-task scenarios to recognize facial expressions, valence, and arousal on static photos. These neural networks extract frame-level features fed into a simple classifier, e.g., linear feed-forward neural network, to predict emotion intensity, compound expressions, action units, facial expressions, and valence/arousal. Experimental results for five tasks from the sixth ABAW challenge demonstrate that our approach lets us significantly improve quality metrics on validation sets compared to existing non-ensemble techniques.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 28 of its 48 references that are in the map. First posted on arXiv 18 Mar 2024.

Builds on

28 of 48 references.

References · 28

  1. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,442
  2. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,905
  3. 2017VGGFace2: A dataset for recognising faces across pose and agecited by 914
  4. 2021MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformercited by 642
  5. 2019MediaPipe: A Framework for Building Perception Pipelinescited by 583
  6. 2017AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wildcited by 492
  7. 2019Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacecited by 222
  8. 2018Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyondcited by 216
  9. 2018MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devicescited by 182
  10. 2021Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Frameworkcited by 174
  11. 2021Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Studycited by 168
  12. 2021Analysing Affective Behavior in the second ABAW2 Competitioncited by 163
16 more
  1. 2022ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challengescited by 156
  2. 2019Face Behavior a la carte: Expressions, Affect and Action Units in a Single Networkcited by 155
  3. 2022Towards Efficient and Scalable Sharpness-Aware Minimizationcited by 129
  4. 2022ABAW: Learning from Synthetic Data & Multi-Task Learning Challengescited by 110
  5. 2024The 6th Affective Behavior Analysis in-the-wild (ABAW) Competitioncited by 78
  6. 2022Killing Two Birds with One Stone:Efficient and Robust Training of Face Recognition CNNs by Partial FCcited by 74
  7. 2023From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videoscited by 39
  8. 2023Multi-modal Facial Affective Analysis based on Masked Autoencodercited by 23
  9. 2023Leveraging TCN and Transformer for effective visual-audio fusion in continuous emotion recognitioncited by 20
  10. 2023Multimodal Continuous Emotion Recognition: A Technical Report for ABAW5cited by 14
  11. 2022Emotion Separation and Recognition from a Facial Expression by Generating the Poker Face with Vision Transformerscited by 9
  12. 2021Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representationcited by 7
  13. 2023Facial Affective Behavior Analysis Method for 5th ABAW Competitioncited by 6
  14. 2023Local Region Perception and Relationship Learning Combined with Feature Fusion for Facial Action Unit Detectioncited by 5
  15. 2023Multimodal Feature Extraction and Fusion for Emotional Reaction Intensity Estimation and Expression Classification in Videos with Transformerscited by 5
  16. 2023A Dual Branch Network for Emotional Reaction Intensity Estimationcited by 2

Built on by

Cited by year

Citing papers per year: 2024: 4; 2025: 4.

8 papers.

  1. 20247th ABAW Competition: Multi-Task Learning and Compound Expression Recognitioncited by 53
  2. 2024Recursive Joint Cross-Modal Attention for Multimodal Fusion in Dimensional Emotion Recognitioncited by 15
  3. 2024Enhancing Facial Expression Recognition through Dual-Direction Attention Mixed Feature Networks: Application to 7th ABAW Challengecited by 8
  4. 2025MAVEN: Multi-modal Attention for Valence-Arousal Emotion Networkcited by 8
  5. 2025Semantic Matters: Multimodal Features for Affective Analysiscited by 5
  6. 2024AUD-TGN: Advancing Action Unit Detection with Temporal Convolution and GPT-2 in Wild Audiovisual Contextscited by 3
  7. 2025V-NAW: Video-based Noise-aware Adaptive Weighting for Facial Expression Recognitioncited by 1
  8. 2025Lightweight Models for Emotional Analysis in Videocited by 0