Micro-expression recognition with supervised contrastive learning

Ruicong Zhi; Jing Hu; Fei Wan

doi:10.1016/j.patrec.2022.09.006

ScienceGate Book Chapters

JOURNAL ARTICLE

Micro-expression recognition with supervised contrastive learning

Ruicong Zhi Jing Hu Fei Wan

Year: 2022 Journal: Pattern Recognition Letters Vol: 163 Pages: 25-31 Publisher: Elsevier BV

DOI: 10.1016/j.patrec.2022.09.006

Get Full-Text PDF Get Analytical Report

Keywords:

Spotting Computer science Artificial intelligence Pattern recognition (psychology) Expression (computer science) Noise (video) Facial expression Facial expression recognition Representation (politics) Dual (grammatical number) Speech recognition Facial recognition system Image (mathematics)

Metrics

Cited By

8.12

FWCI (Field Weighted Citation Impact)

Refs

0.97

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Emotion and Mood Recognition

Social Sciences → Psychology → Experimental and Cognitive Psychology

Gaze Tracking and Assistive Technology

Physical Sciences → Computer Science → Human-Computer Interaction

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Micro-expression recognition with supervised contrastive learning

Metrics

Citation History

Topics

Related Documents

SPCL-MER: Supervised Prototypical Contrastive Learning for Micro-Expression Recognition

Micro-expression recognition using dual-view self-supervised contrastive learning with intensity perception

GSCL-RVT: Generalized supervised contrastive learning with global–local feature fusion for micro-expression recognition

Open-set Recognition with Supervised Contrastive Learning

Micro-expression Recognition based on Bimodal Contrastive Learning