Action unit detection by exploiting spatial-temporal and label-wise attention with transformer

Author:

Wang Lingfeng1,Qi Jin1,Cheng Jian1,Suzuki Kenji2

Affiliation:

1. University of Electronic Science and Technology of China,Chengdu,China

2. Tokyo Institute of Technology,Tokyo,Japan

Publisher

IEEE

Reference23 articles.

1. Face behavior a la carte: Expressions, affect and action units in a single network;kollias,2020

2. Distribution matching for heterogeneous multitask learning: a large-scale face study;kollias,2021

3. Deep Affect Prediction in-the-Wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond

4. Expression, affect, action unit recognition: Aff-wild2, multi-task learning and arcface;kollias,2019

5. Affect analysis in-the-wild: Valence-arousal, expressions, action units and a unified framework;kollias,2021

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1. Facial action units detection using temporal context and feature reassignment;Computer Animation and Virtual Worlds;2024-05

2. A Multi-Teacher Assisted Knowledge Distillation Approach for Enhanced Face Image Authentication;Proceedings of the 2023 ACM International Conference on Multimedia Retrieval;2023-06-12

3. Spatial-Temporal Graph-Based AU Relationship Learning for Facial Action Unit Detection;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06

4. EmotiEffNets for Facial Processing in Video-based Valence-Arousal Prediction, Expression Classification and Action Unit Detection;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06

5. ABAW: Learning from Synthetic Data & Multi-task Learning Challenges;Lecture Notes in Computer Science;2023

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