ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Emotional Reaction Intensity Estimation Challenges

Author:

Kollias Dimitrios1,Tzirakis Panagiotis2,Baird Alice2,Cowen Alan2,Zafeiriou Stefanos3

Affiliation:

1. Queen Mary University of London,UK

2. Hume AI,USA

3. Imperial College London,UK

Publisher

IEEE

Reference92 articles.

1. Affect expression behaviour analysis in the wild using spatio-channel attention and complementary context information;gera,2020

2. A joint cross-attention model for audio-visual fusion in dimensional emotion recognition;rajasekar,2022

3. Alexey Karpov, and Wolfgang Minker. An audio-video deep and transfer learning framework for multimodal emotion recognition in the wild;dresvyanskiy,2020

4. Expression classification using concatenation of deep neural network for the 3rd abaw3 competition;phan,2022

5. Ss-mfar: Semi-supervised multi-task facial affect recognition;gera,2022

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1. Emotion Recognition from Videos Using Multimodal Large Language Models;Future Internet;2024-07-13

2. Emotion Recognition beyond Pixels: Leveraging Facial Point Landmark Meshes;Applied Sciences;2024-04-16

3. Incongruity-Aware Cross-Modal Attention for Audio-Visual Fusion in Dimensional Emotion Recognition;IEEE Journal of Selected Topics in Signal Processing;2024-04

4. Refining Valence-Arousal Estimation with Dual-Stream Label Density Smoothing;2024 IEEE International Conference on Consumer Electronics (ICCE);2024-01-06

5. A Unified Approach to Facial Affect Analysis: the MAE-Face Visual Representation;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06

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