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Found 9 papers, 1 papers with code
Improving Deep Facial Phenotyping for Ultra-rare Disorder Verification Using Model Ensembles
Because of the overall scarcity of patients with ultra-rare disorders, it is infeasible to directly train a model on them.
Few-Shot Meta Learning for Recognizing Facial Phenotypes of Genetic Disorders
Furthermore, we created simple baselines of few-shot meta-learning methods to improve our base feature descriptor.
Are 3D Face Shapes Expressive Enough for Recognising Continuous Emotions and Action Unit Intensities?
We also study how 3D face shapes performed on AU intensity estimation on BP4D and DISFA datasets, and report that 3D face features were on par with 2D appearance features in AUs 4, 6, 10, 12, and 25, but not the entire set of AUs.
Estimating Presentation Competence using Multimodal Nonverbal Behavioral Cues
One approach that can promote efficient development of presentation competence is the automated analysis of human behavior during a speech based on visual and audio features and machine learning.
Multimodal Engagement Analysis from Facial Videos in the Classroom
To best examine student visual engagement in the classroom, we conducted a study utilizing the audiovisual recordings of classes at a secondary school over one and a half month's time, acquired continuous engagement labeling per student (N=15) in repeated sessions, and explored computer vision methods to classify engagement levels from faces in the classroom.
Facial Expression Recognition
Facial Expression Recognition (FER)
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Automated Anonymisation of Visual and Audio Data in Classroom Studies
A possible solution would be to request permission to record the audio-visual recordings of all students (including those who do not voluntarily participate in the study) and to anonymise their data.
Attention Flow: End-to-End Joint Attention Estimation
This paper addresses the problem of understanding joint attention in third-person social scene videos.
Teacher's Perception in the Classroom
The ability for a teacher to engage all students in active learning processes in classroom constitutes a crucial prerequisite for enhancing students achievement.
Self-supervised Learning of Pose Embeddings from Spatiotemporal Relations in Videos
Human pose analysis is presently dominated by deep convolutional networks trained with extensive manual annotations of joint locations and beyond.
