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Found 8 papers, 0 papers with code
MEDIC: A Multimodal Empathy Dataset in Counseling
We also propose three labels (i. e., expression of experience, emotional reaction, and cognitive reaction) to describe the degree of empathy between counselors and their clients.
Emotional Reaction Intensity Estimation Based on Multimodal Data
In this paper, 1. better features are extracted with the SOTA pretrained models.
Facial Affective Behavior Analysis Method for 5th ABAW Competition
Facial affective behavior analysis is important for human-computer interaction.
Multi-Task Learning for Emotion Descriptors Estimation at the fourth ABAW Challenge
The 4th competition on affective behavior analysis in the wild (ABAW) provided images with valence/arousal, expression and action unit labels.
Hand-Assisted Expression Recognition Method from Synthetic Images at the Fourth ABAW Challenge
Learning from synthetic images plays an important role in facial expression recognition task due to the difficulties of labeling the real images, and it is challenging because of the gap between the synthetic images and real images.
Facial Expression Recognition
Facial Expression Recognition (FER)
Facial Action Unit Recognition Based on Transfer Learning
Then we fine-tune the network for facial action unit recognition.
Knowledge-Driven Self-Supervised Representation Learning for Facial Action Unit Recognition
To remedy this, we utilize AU labeling rules defined by the Facial Action Coding System (FACS) to design a novel knowledge-driven self-supervised representation learning framework for AU recognition.
Exploring Adversarial Learning for Deep Semi-Supervised Facial Action Unit Recognition
Specifically, the proposed deep semi-supervised AU recognition approach consists of a deep recognition network and a discriminator D. The deep recognition network R learns facial representations from large-scale facial images and AU classifiers from limited ground truth AU labels.
