Papers Facial Action Unit Detection
“Facial Action Unit Detection” 태그가 달린 논문 101편 · 필터 해제
Spatiotemporal Facial Action Unit Detection using Twin Cycle Autoencoders for Driver Monitoring
Driver monitoring systems (DMS) increasingly rely on facial cues to infer drowsiness, distraction, and cognitive load in real time. Facial Action Units (AUs), grounded in the Facial Action Coding System (FACS), provide a…
Facial Action Unit DetectionUAU-Net: Uncertainty-aware Representation Learning and Evidential Classification for Facial Action Unit Detection
Facial action unit (AU) detection remains challenging because it involves heterogeneous, AU-specific uncertainties arising at both the representation and decision stages. Recent methods have improved discriminative featu…
Facial Action Unit DetectionRepresentation LearningThe Nonverbal Gap: Toward Affective Computer Vision for Safer and More Equitable Online Dating
Online dating has become the dominant way romantic relationships begin, yet current platforms strip the nonverbal cues: gaze, facial expression, body posture, response timing, that humans rely on to signal comfort, disin…
Facial Action Unit DetectionGaze EstimationHierarchical Vision-Language Interaction for Facial Action Unit Detection
Facial Action Unit (AU) detection seeks to recognize subtle facial muscle activations as defined by the Facial Action Coding System (FACS). A primary challenge w.r.t AU detection is the effective learning of discriminati…
Facial Action Unit DetectionRepresentation LearningFAMNet: Integrating 2D and 3D Features for Micro-expression Recognition via Multi-task Learning and Hierarchical Attention
Micro-expressions recognition (MER) has essential application value in many fields, but the short duration and low intensity of micro-expressions (MEs) bring considerable challenges to MER. The current MER methods in dee…
Micro-Expression RecognitionFacial Action Unit DetectionMulti-Task LearningFG 2025 TrustFAA: the First Workshop on Towards Trustworthy Facial Affect Analysis: Advancing Insights of Fairness, Explainability, and Safety (TrustFAA)
With the increasing prevalence and deployment of Emotion AI-powered facial affect analysis (FAA) tools, concerns about the trustworthiness of these systems have become more prominent. This first workshop on "Towards Trus…
Action Unit DetectionDepression DetectionEthicsFacial Action Unit Detection+3AU-TTT: Vision Test-Time Training model for Facial Action Unit Detection
Facial Action Units (AUs) detection is a cornerstone of objective facial expression analysis and a critical focus in affective computing. Despite its importance, AU detection faces significant challenges, such as the hig…
Action Unit DetectionFacial Action Unit DetectionSelf-Supervised LearningDecoupled Doubly Contrastive Learning for Cross Domain Facial Action Unit Detection
Despite the impressive performance of current vision-based facial action unit (AU) detection approaches, they are heavily susceptible to the variations across different domains and the cross-domain AU detection methods a…
Action Unit DetectionContrastive LearningFacial Action Unit DetectionImage GenerationFacial Action Unit Detection by Adaptively Constraining Self-Attention and Causally Deconfounding Sample
Facial action unit (AU) detection remains a challenging task, due to the subtlety, dynamics, and diversity of AUs. Recently, the prevailing techniques of self-attention and causal inference have been introduced to AU det…
Action Unit DetectionCausal InferenceFacial Action Unit DetectionTowards Unified Facial Action Unit Recognition Framework by Large Language Models
Facial Action Units (AUs) are of great significance in the realm of affective computing. In this paper, we propose AU-LLaVA, the first unified AU recognition framework based on the Large Language Model (LLM). AU-LLaVA co…
Facial Action Unit DetectionLanguage ModelingLanguage ModellingLarge Language ModelTowards End-to-End Explainable Facial Action Unit Recognition via Vision-Language Joint Learning
Facial action units (AUs), as defined in the Facial Action Coding System (FACS), have received significant research interest owing to their diverse range of applications in facial state analysis. Current mainstream FAU r…
Facial Action Unit DetectionRepresentation LearningNorface: Improving Facial Expression Analysis by Identity Normalization
Facial Expression Analysis remains a challenging task due to unexpected task-irrelevant noise, such as identity, head pose, and background. To address this issue, this paper proposes a novel framework, called Norface, th…
ClassificationEmotion RecognitionFacial Action Unit DetectionFacial Emotion Recognition+2Representation Learning and Identity Adversarial Training for Facial Behavior Understanding
Facial Action Unit (AU) detection has gained significant attention as it enables the breakdown of complex facial expressions into individual muscle movements. In this paper, we revisit two fundamental factors in AU detec…
Facial Action Unit DetectionFacial Expression Recognition (FER)Representation LearningMulti-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 located in the same/close facial regions sh…
Facial Action Unit DetectionAUD-TGN: Advancing Action Unit Detection with Temporal Convolution and GPT-2 in Wild Audiovisual Contexts
Leveraging the synergy of both audio data and visual data is essential for understanding human emotions and behaviors, especially in in-the-wild setting. Traditional methods for integrating such multimodal information of…
Action Unit DetectionFacial Action Unit DetectionLeveraging Synthetic Data for Generalizable and Fair Facial Action Unit Detection
Facial action unit (AU) detection is a fundamental block for objective facial expression analysis. Supervised learning approaches require a large amount of manual labeling which is costly. The limited labeled data are al…
Action Unit DetectionDomain AdaptationFacial Action Unit DetectionFairnessGPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing
Multimodal large language models (MLLMs) are designed to process and integrate information from multiple sources, such as text, speech, images, and videos. Despite its success in language understanding, it is critical to…
Emotion RecognitionFacial Action Unit DetectionFacial Expression RecognitionHeart rate estimation+2AUFormer: Vision Transformers are Parameter-Efficient Facial Action Unit Detectors
Facial Action Units (AU) is a vital concept in the realm of affective computing, and AU detection has always been a hot research topic. Existing methods suffer from overfitting issues due to the utilization of a large nu…
Facial Action Unit DetectionTransfer LearningContrastive Learning of Person-independent Representations for Facial Action Unit Detection
Facial action unit (AU) detection, aiming to classify AU present in the facial image, has long suffered from insufficient AU annotations. In this paper, we aim to mitigate this data scarcity issue by learning AU represen…
Action Unit DetectionContrastive LearningFacial Action Unit DetectionRepresentation LearningLearning Contrastive Feature Representations for Facial Action Unit Detection
For the Facial Action Unit (AU) detection task, accurately capturing the subtle facial differences between distinct AUs is essential for reliable detection. Additionally, AU detection faces challenges from class imbalanc…
Action Unit DetectionBinary ClassificationContrastive LearningFacial Action Unit Detection