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In this paper, we present our contribution to ABAW facial expression challenge. We report the proposed system and the official challenge results adhering to the challenge protocol. Using end-to-end deep learning and benefiting from transfer…

机器学习 · 计算机科学 2020-11-03 Denis Dresvyanskiy , Elena Ryumina , Heysem Kaya , Maxim Markitantov , Alexey Karpov , Wolfgang Minker

For computers to recognize human emotions, expression classification is an equally important problem in the human-computer interaction area. In the 3rd Affective Behavior Analysis In-The-Wild competition, the task of expression…

计算机视觉与模式识别 · 计算机科学 2022-04-11 Kim Ngan Phan , Hong-Hai Nguyen , Van-Thong Huynh , Soo-Hyung Kim

Emotions recognition is the task of recognizing people's emotions. Usually it is achieved by analyzing expression of peoples faces. There are two ways for representing emotions: The categorical approach and the dimensional approach by using…

机器学习 · 计算机科学 2019-12-17 Alvertos Benroumpi , Dimitrios Kollias

Human emotion recognition plays an important role in human-computer interaction. In this paper, we present our approach to the Valence-Arousal (VA) Estimation Challenge, Expression (Expr) Classification Challenge, and Action Unit (AU)…

计算机视觉与模式识别 · 计算机科学 2023-09-07 Weiwei Zhou , Jiada Lu , Zhaolong Xiong , Weifeng Wang

Facial Expression Recognition(FER) is one of the most important topic in Human-Computer interactions(HCI). In this work we report details and experimental results about a facial expression recognition method based on state-of-the-art…

计算机视觉与模式识别 · 计算机科学 2021-01-25 Donato Cafarelli , Fabio Valerio Massoli , Fabrizio Falchi , Claudio Gennaro , Giuseppe Amato

The technical report presents our emotion recognition pipeline for high-dimensional emotion task (A-VB High) in The ACII Affective Vocal Bursts (A-VB) 2022 Workshop \& Competition. Our proposed method contains three stages. Firstly, we…

声音 · 计算机科学 2022-09-27 Dang-Linh Trinh , Minh-Cong Vo , Guee-Sang Lee

This paper describes our submission to the fourth Affective Behavior Analysis (ABAW) competition. We proposed a hybrid CNN-Transformer model for the Multi-Task-Learning (MTL) and Learning from Synthetic Data (LSD) task. Experimental results…

计算机视觉与模式识别 · 计算机科学 2022-07-22 Lingfeng Wang , Haocheng Li , Chunyin Liu

Developing machine learning algorithms to understand person-to-person engagement can result in natural user experiences for communal devices such as Amazon Alexa. Among other cues such as voice activity and gaze, a person's audio-visual…

音频与语音处理 · 电气工程与系统科学 2020-12-02 Srinivas Parthasarathy , Shiva Sundaram

Facial Emotion Analysis (FEA) extends traditional facial emotion recognition by incorporating explainable, fine-grained reasoning. The task integrates three subtasks: emotion recognition, facial Action Unit (AU) recognition, and AU-based…

计算机视觉与模式识别 · 计算机科学 2025-11-14 Jiulong Wu , Yucheng Shen , Lingyong Yan , Haixin Sun , Deguo Xia , Jizhou Huang , Min Cao

This paper presents the results of the SUN team for the Compound Expressions Recognition Challenge of the 6th ABAW Competition. We propose a novel audio-visual method for compound expression recognition. Our method relies on emotion…

计算机视觉与模式识别 · 计算机科学 2024-04-01 Elena Ryumina , Maxim Markitantov , Dmitry Ryumin , Heysem Kaya , Alexey Karpov

This paper describes the proposed methodology, data used and the results of our participation in the ChallengeTrack 2 (Expr Challenge Track) of the Affective Behavior Analysis in-the-wild (ABAW) Competition 2020. In this competition, we…

计算机视觉与模式识别 · 计算机科学 2020-10-06 Hafiq Anas , Bacha Rehman , Wee Hong Ong

Facial expression in-the-wild is essential for various interactive computing domains. Especially, "Emotional Reaction Intensity" (ERI) is an important topic in the facial expression recognition task. In this paper, we propose a…

计算机视觉与模式识别 · 计算机科学 2023-03-17 JiYeon Oh , Daun Kim , Jae-Yeop Jeong , Yeong-Gi Hong , Jin-Woo Jeong

Understanding and predicting human behavior has emerged as a core capability in various AI application domains such as autonomous driving, smart healthcare, surveillance systems, and social robotics. This paper defines the technical…

人工智能 · 计算机科学 2025-05-07 Kanghyun Jo , Jehwan Choi , Kwanho Kim , Seongmin Kim , Duy-Linh Nguyen , Xuan-Thuy Vo , Adri Priadana , Tien-Dat Tran

Automatic emotion recognition is a challenging task. In this paper, we present our effort for the audio-video based sub-challenge of the Emotion Recognition in the Wild (EmotiW) 2018 challenge, which requires participants to assign a single…

计算机视觉与模式识别 · 计算机科学 2018-09-18 Zheng Lian , Ya Li , Jianhua Tao , Jian Huang

Facial Action Coding System is an important approach of facial expression analysis.This paper describes our submission to the third Affective Behavior Analysis (ABAW) 2022 competition. We proposed a transfomer based model to detect facial…

计算机视觉与模式识别 · 计算机科学 2022-03-29 Lingfeng Wang , Shisen Wang , Jin Qi

The task of predicting affective information in the wild such as seven basic emotions or action units from human faces has gradually become more interesting due to the accessibility and availability of massive annotated datasets. In this…

计算机视觉与模式识别 · 计算机科学 2021-07-12 Phan Tran Dac Thinh , Hoang Manh Hung , Hyung-Jeong Yang , Soo-Hyung Kim , Guee-Sang Lee

Much of the work on automatic facial expression recognition relies on databases containing a certain number of emotion classes and their exaggerated facial configurations (generally six prototypical facial expressions), based on Ekman's…

计算机视觉与模式识别 · 计算机科学 2020-09-29 Wenjing Yan , Shan Li , Chengtao Que , JiQuan Pei , Weihong Deng

The paper describes our proposed methodology for the seven basic expression classification track of Affective Behavior Analysis in-the-wild (ABAW) Competition 2021. In this task, facial expression recognition (FER) methods aim to classify…

计算机视觉与模式识别 · 计算机科学 2021-07-13 Shuyi Mao , Xinqi Fan , Xiaojiang Peng

Dynamic emotion recognition in the wild remains challenging due to the transient nature of emotional expressions and temporal misalignment of multi-modal cues. Traditional approaches predict valence and arousal and often overlook the…

This paper describes an approach to the facial action units detections. The involved action units (AU) include AU1 (Inner Brow Raiser), AU2 (Outer Brow Raiser), AU4 (Brow Lowerer), AU6 (Cheek Raise), AU12 (Lip Corner Puller), AU15 (Lip…

计算机视觉与模式识别 · 计算机科学 2020-02-11 Xianpeng Ji , Yu Ding , Lincheng Li , Yu Chen , Changjie Fan