Multi-scale dynamic and hierarchical relationship modeling for facial action units recognition
Human facial action units (AUs) are mutually related in a hierarchical manner as not only
they are associated with each other in both spatial and temporal domains but also AUs …
they are associated with each other in both spatial and temporal domains but also AUs …
Weakly-supervised text-driven contrastive learning for facial behavior understanding
Contrastive learning has shown promising potential for learning robust representations by
utilizing unlabeled data. However, constructing effective positive-negative pairs for …
utilizing unlabeled data. However, constructing effective positive-negative pairs for …
A joint local spatial and global temporal CNN-Transformer for dynamic facial expression recognition
Unlike conventional video action recognition, Dynamic Facial Expression Recognition
(DFER) tasks exhibit minimal spatial movement of objects. Addressing this distinctive …
(DFER) tasks exhibit minimal spatial movement of objects. Addressing this distinctive …
Toward robust facial action units' detection
Facial action unit (AU) detection plays an important role in performing facial behavioral
analysis of raw video inputs. Overall, there are three key factors that contribute toward the …
analysis of raw video inputs. Overall, there are three key factors that contribute toward the …
Knowledge-spreader: Learning semi-supervised facial action dynamics by consistifying knowledge granularity
Recent studies on dynamic facial action unit (AU) detection have extensively relied on
dense annotations. However, manual annotations are difficult, time-consuming, and costly …
dense annotations. However, manual annotations are difficult, time-consuming, and costly …
Reactionet: Learning high-order facial behavior from universal stimulus-reaction by dyadic relation reasoning
Diverse visual stimuli can evoke various human affective states, which are usually
manifested in an individual's muscular actions and facial expressions. In lab-controlled …
manifested in an individual's muscular actions and facial expressions. In lab-controlled …
Multimodal channel-mixing: Channel and spatial masked autoencoder on facial action unit detection
Recent studies have focused on utilizing multi-modal data to develop robust models for
facial Action Unit (AU) detection. However, the heterogeneity of multi-modal data poses …
facial Action Unit (AU) detection. However, the heterogeneity of multi-modal data poses …
Disagreement matters: Exploring internal diversification for redundant attention in generic facial action analysis
This paper demonstrates the effectiveness of a diversification mechanism for building a
more robust multi-attention system in generic facial action analysis. While previous multi …
more robust multi-attention system in generic facial action analysis. While previous multi …
Self Decoupling-Reconstruction Network for Facial Expression Recognition
Facial Expression Recognition (FER) poses significant challenges due to various imaging
conditions, including diverse head poses, lighting conditions, resolutions, and occlusions …
conditions, including diverse head poses, lighting conditions, resolutions, and occlusions …
Knowledge-spreader: Learning facial action unit dynamics with extremely limited labels
Recent studies on the automatic detection of facial action unit (AU) have extensively relied
on large-sized annotations. However, manually AU labeling is difficult, time-consuming, and …
on large-sized annotations. However, manually AU labeling is difficult, time-consuming, and …