Deep learning for depression recognition with audiovisual cues: A review
With the acceleration of the pace of work and life, people are facing more and more
pressure, which increases the probability of suffering from depression. However, many …
pressure, which increases the probability of suffering from depression. However, many …
Self-trained deep ordinal regression for end-to-end video anomaly detection
Video anomaly detection is of critical practical importance to a variety of real applications
because it allows human attention to be focused on events that are likely to be of interest, in …
because it allows human attention to be focused on events that are likely to be of interest, in …
Transformer-based multimodal feature enhancement networks for multimodal depression detection integrating video, audio and remote photoplethysmograph signals
Depression stands as one of the most widespread psychological disorders and has
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …
Automatic depression recognition using CNN with attention mechanism from videos
Artificial intelligence (AI) has incorporated various automatic systems and frameworks to
diagnose the severity of depression using hand-crafted features. However, process of …
diagnose the severity of depression using hand-crafted features. However, process of …
Spatial–temporal attention network for depression recognition from facial videos
Recent studies focus on the utilization of deep learning approaches to recognize depression
from facial videos. However, these approaches have been hindered by their limited …
from facial videos. However, these approaches have been hindered by their limited …
Multimodal spatiotemporal representation for automatic depression level detection
Physiological studies have shown that there are some differences in speech and facial
activities between depressive and healthy individuals. Based on this fact, we propose a …
activities between depressive and healthy individuals. Based on this fact, we propose a …
Exploring racial bias within face recognition via per-subject adversarially-enabled data augmentation
Whilst face recognition applications are becoming increasingly prevalent within our daily
lives, leading approaches in the field still suffer from performance bias to the detriment of …
lives, leading approaches in the field still suffer from performance bias to the detriment of …
Deep multi-modal network based automated depression severity estimation
Depression is a severe mental illness that impairs a person's capacity to function normally in
personal and professional life. The assessment of depression usually requires a …
personal and professional life. The assessment of depression usually requires a …
PRA-Net: Part-and-Relation Attention Network for depression recognition from facial expression
Artificial intelligence methods are widely applied to depression recognition and provide an
objective solution. Many effective automated methods for detecting depression use facial …
objective solution. Many effective automated methods for detecting depression use facial …
Integrating deep facial priors into landmarks for privacy preserving multimodal depression recognition
Automatic depression diagnosis is a challenging problem, that requires integrating spatial-
temporal information and extracting features from audio-visual signals. In terms of privacy …
temporal information and extracting features from audio-visual signals. In terms of privacy …