Facial Action Unit Detection
17 papers with code • 2 benchmarks • 4 datasets
Facial action unit detection is the task of detecting action units from a video of a face - for example, lip tightening and cheek raising.
( Image credit: Self-supervised Representation Learning from Videos for Facial Action Unit Detection )
Libraries
Use these libraries to find Facial Action Unit Detection models and implementations
DISFA
BP4D
CANDOR Corpus
Thermal Face Database
Latest papers with no code
Biomechanics-Guided Facial Action Unit Detection Through Force Modeling
In this paper, we propose a biomechanics-guided AU detection approach, where facial muscle activation forces are modelled, and are employed to predict AU activation.
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.
FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detection
Our model consists of a hybrid network of convolution and transformer blocks to learn per-AU features and to model AU co-occurrences.
Facial Action Unit Detection and Intensity Estimation from Self-supervised Representation
As a fine-grained and local expression behavior measurement, facial action unit (FAU) analysis (e. g., detection and intensity estimation) has been documented for its time-consuming, labor-intensive, and error-prone annotation.
Global-to-local Expression-aware Embeddings for Facial Action Unit Detection
Then, AU feature maps and their corresponding AU masks are multiplied to generate AU masked features focusing on local facial region.
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.
Causal Intervention for Subject-Deconfounded Facial Action Unit Recognition
Subject-invariant facial action unit (AU) recognition remains challenging for the reason that the data distribution varies among subjects.
Weakly Supervised Regional and Temporal Learning for Facial Action Unit Recognition
Automatic facial action unit (AU) recognition is a challenging task due to the scarcity of manual annotations.
Facial Action Unit Recognition Based on Transfer Learning
Then we fine-tune the network for facial action unit recognition.
Facial Action Unit Recognition With Multi-models Ensembling
The Affective Behavior Analysis in-the-wild (ABAW) 2022 Competition gives Affective Computing a large promotion.
