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Micro-Expression Recognition Based on Attribute Information Embedding and Cross-modal Contrastive Learning

arXiv 2205.14643 ↗First posted 29 May 2022cs.CV cs.AI cs.LGcited by 0

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Abstract (arXiv)

Facial micro-expressions recognition has attracted much attention recently. Micro-expressions have the characteristics of short duration and low intensity, and it is difficult to train a high-performance classifier with the limited number of existing micro-expressions. Therefore, recognizing micro-expressions is a challenge task. In this paper, we propose a micro-expression recognition method based on attribute information embedding and cross-modal contrastive learning. We use 3D CNN to extract RGB features and FLOW features of micro-expression sequences and fuse them, and use BERT network to extract text information in Facial Action Coding System. Through cross-modal contrastive loss, we embed attribute information in the visual network, thereby improving the representation ability of micro-expression recognition in the case of limited samples. We conduct extensive experiments in CASME II and MMEW databases, and the accuracy is 77.82% and 71.04%, respectively. The comparative experiments show that this method has better recognition effect than other methods for micro-expression recognition.

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References · 16

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  6. 2022Video-based Facial Micro-Expression Analysis: A Survey of Datasets, Features and Algorithmscited by 51
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  8. 2015Towards Reading Hidden Emotions: A comparative Study of Spontaneous Micro-expression Spotting and Recognition Methodscited by 37
  9. 2018Enriched Long-term Recurrent Convolutional Network for Facial Micro-Expression Recognitioncited by 27
  10. 2019Relation Modeling with Graph Convolutional Networks for Facial Action Unit Detectioncited by 25
  11. 2019SAMM Long Videos: A Spontaneous Facial Micro- and Macro-Expressions Datasetcited by 25
  12. 2018Feature Space Transfer for Data Augmentationcited by 21
4 more
  1. 2020Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolutioncited by 21
  2. 2019Spontaneous Facial Micro-Expression Recognition using 3D Spatiotemporal Convolutional Neural Networkscited by 18
  3. 2019Micro-expression detection in long videos using optical flow and recurrent neural networkscited by 16
  4. 2017Attentive Recurrent Comparatorscited by 13

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