Cited by

• 2022Deep Learning for Micro-Expression Recognition: A Survey158 cited
• 2020GEME: Dual-stream multi-task GEnder-based micro-expression recognition141 cited
• 2021A two-stage 3D CNN based learning method for spontaneous micro-expression recognition141 cited
• 2019Recognizing Spontaneous Micro-Expression Using a Three-Stream Convolutional Neural Network122 cited
• 2019Recognizing Facial Expressions Using a Shallow Convolutional Neural Network110 cited
• 2018SMEConvNet: A Convolutional Neural Network for Spotting Spontaneous Facial Micro-Expression From Long Videos94 cited
• 2023Facial Micro-Expressions: An Overview85 cited
• 2022An Overview of Facial Micro-Expression Analysis: Data, Methodology and Challenge78 cited
• 2022Using Facial Micro-Expressions in Combination With EEG and Physiological Signals for Emotion Recognition69 cited
• 2019Micro-expression detection in long videos using optical flow and recurrent neural networks63 cited
• 2022Driver Emotions Recognition Based on Improved Faster R-CNN and Neural Architectural Search Network59 cited
• 2021Shallow Optical Flow Three-Stream CNN For Macro- And Micro-Expression Spotting From Long Videos58 cited
• 2019Extended Local Binary Patterns for Efficient and Robust Spontaneous Facial Micro-Expression Recognition57 cited
• 2020A survey of micro-expression recognition55 cited
• 2021Micro-expression spotting: A new benchmark55 cited
• 2021DRER: Deep Learning–Based Driver’s Real Emotion Recognizer55 cited