Papers Valence Estimation
“Valence Estimation” 태그가 달린 논문 10편 · 필터 해제
Facial Geometric Feature Extraction for Dimensional Emotion Analysis Using Genetic Programming
Geometric features derived from single static images have the potential to be highly effective for facial emotion analysis, as shape, structure, and spatial relationships are key factors. However, these aspects are rarel…
Arousal EstimationContinuous Affect EstimationEmotion RecognitionValence EstimationMEEG and AT-DGNN: Improving EEG Emotion Recognition with Music Introducing and Graph-based Learning
We present the MEEG dataset, a multi-modal collection of music-induced electroencephalogram (EEG) recordings designed to capture emotional responses to various musical stimuli across different valence and arousal levels.…
Arousal EstimationEEGEEG Emotion RecognitionElectroencephalogram (EEG)+5CAGE: Circumplex Affect Guided Expression Inference
Understanding emotions and expressions is a task of interest across multiple disciplines, especially for improving user experiences. Contrary to the common perception, it has been shown that emotions are not discrete ent…
Arousal EstimationDominance EstimationEmotion RecognitionFacial Expression Recognition (FER)+1Real-time EEG-based Emotion Recognition Model using Principal Component Analysis and Tree-based Models for Neurohumanities
Within the field of Humanities, there is a recognized need for educational innovation, as there are currently no reported tools available that enable individuals to interact with their environment to create an enhanced l…
Arousal EstimationDominance EstimationEEGEEG Emotion Recognition+3Personalized Adaptation with Pre-trained Speech Encoders for Continuous Emotion Recognition
There are individual differences in expressive behaviors driven by cultural norms and personality. This between-person variation can result in reduced emotion recognition performance. Therefore, personalization is an imp…
Emotion RecognitionSpeech Emotion RecognitionValence EstimationPre-trained Model Representations and their Robustness against Noise for Speech Emotion Analysis
Pre-trained model representations have demonstrated state-of-the-art performance in speech recognition, natural language processing, and other applications. Speech models, such as Bidirectional Encoder Representations fr…
Emotion RecognitionKnowledge Distillationspeech-recognitionSpeech Recognition+1Speech Emotion: Investigating Model Representations, Multi-Task Learning and Knowledge Distillation
Estimating dimensional emotions, such as activation, valence and dominance, from acoustic speech signals has been widely explored over the past few years. While accurate estimation of activation and dominance from speech…
Knowledge DistillationMulti-Task LearningValence EstimationTopological EEG Nonlinear Dynamics Analysis for Emotion Recognition
Emotional recognition through exploring the electroencephalography (EEG) characteristics has been widely performed in recent studies. Nonlinear analysis and feature extraction methods for understanding the complex dynami…
Arousal EstimationDominance EstimationEEGElectroencephalogram (EEG)+6Pre-training strategies and datasets for facial representation learning
What is the best way to learn a universal face representation? Recent work on Deep Learning in the area of face analysis has focused on supervised learning for specific tasks of interest (e.g. face recognition, facial la…
3D Face Reconstruction3D Facial Landmark LocalizationArousal EstimationEmotion Recognition+9Exploiting multi-CNN features in CNN-RNN based Dimensional Emotion Recognition on the OMG in-the-wild Dataset
This paper presents a novel CNN-RNN based approach, which exploits multiple CNN features for dimensional emotion recognition in-the-wild, utilizing the One-Minute Gradual-Emotion (OMG-Emotion) dataset. Our approach inclu…
Arousal EstimationEmotion RecognitionValence Estimation