Micro-Expression Recognition
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Benchmarks
CASME II
Most implemented
GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing
Dual-stream shallow networks for facial micro-expression recognition
Enriched Long-term Recurrent Convolutional Network for Facial Micro-Expression Recognition
MOL: Joint Estimation of Micro-Expression, Optical Flow, and Landmark via Transformer-Graph-Style Convolution
Papers
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 Recognition