KVDERW Dataset : Korean Video Dataset For Emotion Recognition in the wild (KVDERW)
KVDERW database contains video clips collected from 41 Korean movies. The clips were annotated by six Korean evaluators. The database has a main face designated in every frame of each clip to provide more clear information about the object for recognition. Each clip has clear emotion conditions to facilitate easy for training and the development of emotion recognition models. This dataset provides information about the changes in face and background. This is appropriate for models about emotion recognition using facial expression, head pose and background. Read more..
SADVAW Dataset : Stress Analysis with Dimensions of Valence and Arousal in the Wild (SADVAW)
The SADVAW dataset is constructed to evaluate multiple stress levels in continuous dimensions of valence and arousal based on facial features. The SADVAW dataset consists of 1236 video clips extracted from 41 Korean movies. Video clips are extracted from many characters with different backgrounds, closer to the real-world environment. The video clips were evaluated on a 9-level scale for each stress, valence, and arousal class. Read more..
The Physiological Dataset for Multimodal Emotion Recognition with Personality as a Context (PhyMER) dataset consists of multimodal physiological data for Emotion recognition. The PhyMER dataset consists of the recorded physiological signals, such as Electroencephalogram(EEG), Electrodermal Activity(EDA), Blood Pulse Volume(BVP), Heart Rate(HR), Peripheral Skin Temperature(TEMP), participants’ personality information, and emotion annotations in terms of Arousal, Valence, and seven basic emotions. Read more..
The Korean Drama Scene Transcript dataset for Emotion Recognition (KD-EmoR) is a text-based conversation dataset labeled with three classes of complex emotions: euphoria, dysphoria, and neutral, in the scenes of a television drama to build a publicly available dataset for further research. Read more..
GCE Dateset: Audio-Visual Dataset for Group Cohesion and Emotion Analysis (GCE)
The Audio-Visual Dataset for Group Cohesion and Emotion Analysis (GCE) focuses on the recognition of group cohesion and group emotion. Group cohesion and emotion are important in human interactions and relationships. Especially the comprehension of group cohesion and emotion becomes essential when individuals sustain relationships to meet their needs and objectives. Read more..