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Found 8 papers, 0 papers with code
AUD-TGN: Advancing Action Unit Detection with Temporal Convolution and GPT-2 in Wild Audiovisual Contexts
Leveraging the synergy of both audio data and visual data is essential for understanding human emotions and behaviors, especially in in-the-wild setting.
Compound Expression Recognition via Multi Model Ensemble
Compound Expression Recognition (CER) plays a crucial role in interpersonal interactions.
Multimodal Fusion Method with Spatiotemporal Sequences and Relationship Learning for Valence-Arousal Estimation
This paper presents our approach for the VA (Valence-Arousal) estimation task in the ABAW6 competition.
Exploring Facial Expression Recognition through Semi-Supervised Pretraining and Temporal Modeling
Facial Expression Recognition (FER) plays a crucial role in computer vision and finds extensive applications across various fields.
Facial Expression Recognition
Facial Expression Recognition (FER)
Efficient Feature Extraction and Late Fusion Strategy for Audiovisual Emotional Mimicry Intensity Estimation
In this paper, we present the solution to the Emotional Mimicry Intensity (EMI) Estimation challenge, which is part of 6th Affective Behavior Analysis in-the-wild (ABAW) Competition. The EMI Estimation challenge task aims to evaluate the emotional intensity of seed videos by assessing them from a set of predefined emotion categories (i. e., "Admiration", "Amusement", "Determination", "Empathic Pain", "Excitement" and "Joy").
A Dual Branch Network for Emotional Reaction Intensity Estimation
Emotional Reaction Intensity(ERI) estimation is an important task in multimodal scenarios, and has fundamental applications in medicine, safe driving and other fields.
Exploring Large-scale Unlabeled Faces to Enhance Facial Expression Recognition
Facial Expression Recognition (FER) is an important task in computer vision and has wide applications in human-computer interaction, intelligent security, emotion analysis, and other fields.
Local Region Perception and Relationship Learning Combined with Feature Fusion for Facial Action Unit Detection
Human affective behavior analysis plays a vital role in human-computer interaction (HCI) systems.
