Papers Micro-Expression Recognition
“Micro-Expression Recognition” 태그가 달린 논문 99편 · 필터 해제
AU-Guided Synthetic Video Generation for Micro-Expression Recognition
Micro-expression recognition is limited by the small scale, narrow demographic coverage, and restricted emotion labels of existing datasets. We introduce EquiME, a synthetic micro-expression dataset built from AU-guided …
Micro-Expression RecognitionVideo GenerationSTAG: Spatio-temporal Evolving Structural Representation of Action Units for Micro-expression Recognition
Micro-expression recognition is challenging due to subtle and short-lived facial muscle movements. Existing methods rely heavily on apex-onset frames, overlook fine-grained inter-frame dynamics, and separately model spat…
Micro-Expression RecognitionComputational EfficiencyRelational ReasoningSpatial ReasoningSAC$^2$-Net: Semantic Anchoring and Complementary-Consensus Fusion for Multimodal Micro-Expression Recognition
Micro-expression recognition (MER) is challenging due to subtle facial movements, limited data, and the ambiguous relationship between Action Units (AUs) and emotion categories. Optical flow and motion magnification are …
Micro-Expression RecognitionCDER-SME: A Cross-Device Event-RGB Micro-Expression Dataset under Multi-Level Stress Induction
Micro-expression recognition (MER) in realistic scenarios demands high temporal sensitivity and ecological validity, yet existing benchmarks are largely constrained to laboratory-controlled settings and rigid hardware-co…
Micro-Expression RecognitionMEDN: Motion-Emotion Feature Decoupling Network for Micro-Expression Recognition
Unlike macro-expression, micro-expression does not follow a strictly consistent mapping rule between emotions and Action Units (AUs). As a result, some micro-expressions share identical AUs yet represent completely oppos…
Micro-Expression RecognitionEPIR: An Efficient Patch Tokenization, Integration and Representation Framework for Micro-expression Recognition
Micro-expression recognition can obtain the real emotion of the individual at the current moment. Although deep learning-based methods, especially Transformer-based methods, have achieved impressive results, these method…
Micro-Expression RecognitionDual-View Optical Flow for 4D Micro-Expression Recognition - A Multi-Stream Fusion Attention Approach
Micro-expression recognition is vital for affective computing but remains challenging due to the extremely brief, low-intensity facial motions involved and the high-dimensional nature of 4D mesh data. To address these ch…
Micro-Expression RecognitionEvaluating and Correcting Human Annotation Bias in Dynamic Micro-Expression Recognition
Existing manual labeling of micro-expressions is subject to errors in accuracy, especially in cross-cultural scenarios where deviation in labeling of key frames is more prominent. To address this issue, this paper presen…
Micro-Expression RecognitionMicro-expression Recognition Based on Dual-branch Feature Extraction and Fusion
Micro-expressions, characterized by transience and subtlety, pose challenges to existing optical flow-based recognition methods. To address this, this paper proposes a dual-branch micro-expression feature extraction netw…
Micro-Expression RecognitionSRFlow: A Dataset and Regularization Model for High-Resolution Facial Optical Flow via Splatting Rasterization
Facial optical flow supports a wide range of tasks in facial motion analysis. However, the lack of high-resolution facial optical flow datasets has hindered progress in this area. In this paper, we introduce Splatting Ra…
Micro-Expression RecognitionOptical Flow EstimationDEFT-LLM: Disentangled Expert Feature Tuning for Micro-Expression Recognition
Micro expression recognition (MER) is crucial for inferring genuine emotion. Applying a multimodal large language model (MLLM) to this task enables spatio-temporal analysis of facial motion and provides interpretable des…
Micro-Expression RecognitionImproving Micro-Expression Recognition with Phase-Aware Temporal Augmentation
Micro-expressions (MEs) are brief, involuntary facial movements that reveal genuine emotions, typically lasting less than half a second. Recognizing these subtle expressions is critical for applications in psychology, se…
Micro-Expression RecognitionA Novel Combined Optical Flow Approach for Comprehensive Micro-Expression Recognition
Facial micro-expressions are brief, involuntary facial movements that reveal hidden emotions. Most Micro-Expression Recognition (MER) methods that rely on optical flow typically focus on the onset-to-apex phase, neglecti…
Micro-Expression RecognitionDIANet: A Phase-Aware Dual-Stream Network for Micro-Expression Recognition via Dynamic Images
Micro-expressions are brief, involuntary facial movements that typically last less than half a second and often reveal genuine emotions. Accurately recognizing these subtle expressions is critical for applications in psy…
Micro-Expression RecognitionAdaptive Fusion Network with Temporal-Ranked and Motion-Intensity Dynamic Images for Micro-expression Recognition
Micro-expressions (MEs) are subtle, transient facial changes with very low intensity, almost imperceptible to the naked eye, yet they reveal a person genuine emotion. They are of great value in lie detection, behavioral …
Micro-Expression RecognitionFMANet: A Novel Dual-Phase Optical Flow Approach with Fusion Motion Attention Network for Robust Micro-expression Recognition
Facial micro-expressions, characterized by their subtle and brief nature, are valuable indicators of genuine emotions. Despite their significance in psychology, security, and behavioral analysis, micro-expression recogni…
Micro-Expression RecognitionMicro-Expression Recognition via Fine-Grained Dynamic Perception
Facial micro-expression recognition (MER) is a challenging task, due to the transience, subtlety, and dynamics of micro-expressions (MEs). Most existing methods resort to hand-crafted features or deep networks, in which …
Micro-Expression RecognitionRepresentation LearningApex-Centered Spatio-Temporal Rank Pooling and Gradient Attention for Micro-Expression Recognition
Micro-expression recognition (MER) is a challenging task due to the subtle and fleeting nature of micro-expressions. Traditional input modalities, such as Apex Frame, Optical Flow, and Dynamic Image, often fail to adequa…
Micro-Expression RecognitionFAMNet: 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 LearningExploring Spatial-Temporal Dynamics in Event-based Facial Micro-Expression Analysis
Micro-expression analysis has applications in domains such as Human-Robot Interaction and Driver Monitoring Systems. Accurately capturing subtle and fast facial movements remains difficult when relying solely on RGB came…
Micro-Expression Recognition