# MMNet: Muscle motion-guided network for micro-expression recognition

arXiv: https://arxiv.org/abs/2201.05297 · HTML: https://mlsanity.com/paper/2201.05297/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 37 references that are in the map.
- First posted on arXiv 14 Jan 2022.

## Builds on (most cited first, 10 of 10)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [CBAM: Convolutional Block Attention Module](https://mlsanity.com/paper/1807.06521/) (2018)
- [AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild](https://mlsanity.com/paper/1708.03985/) (2017)
- [Deep Facial Expression Recognition: A Survey](https://mlsanity.com/paper/1804.08348/) (2018)
- [OFF-ApexNet on Micro-expression Recognition System](https://mlsanity.com/paper/1805.08699/) (2018)
- [Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition](https://mlsanity.com/paper/1902.03634/) (2019)
- [Towards Reading Hidden Emotions: A comparative Study of Spontaneous Micro-expression Spotting and Recognition Methods](https://mlsanity.com/paper/1511.00423/) (2015)
- [SMA-STN: Segmented Movement-Attending Spatiotemporal Network forMicro-Expression Recognition](https://mlsanity.com/paper/2010.09342/) (2020)
- [Sparsity in Dynamics of Spontaneous Subtle Emotions: Analysis & Application](https://mlsanity.com/paper/1601.04805/) (2016)

## Built on by (most cited first, 18 of 18)

- [Data Leakage and Evaluation Issues in Micro-Expression Analysis](https://mlsanity.com/paper/2211.11425/) (2022)
- [FacialFlowNet: Advancing Facial Optical Flow Estimation with a Diverse Dataset and a Decomposed Model](https://mlsanity.com/paper/2409.05396/) (2024)
- [PosMLP-Video: Spatial and Temporal Relative Position Encoding for Efficient Video Recognition](https://mlsanity.com/paper/2407.02934/) (2024)
- [Adaptive Temporal Motion Guided Graph Convolution Network for Micro-expression Recognition](https://mlsanity.com/paper/2406.08997/) (2024)
- [MELLM: A Flow-Guided Large Language Model for Micro-Expression Understanding](https://mlsanity.com/paper/2505.07007/) (2025)
- [FED-PsyAU: Privacy-Preserving Micro-Expression Recognition via Psychological AU Coordination and Dynamic Facial Motion Modeling](https://mlsanity.com/paper/2507.20557/) (2025)
- [Rethinking Key-frame-based Micro-expression Recognition: A Robust and Accurate Framework Against Key-frame Errors](https://mlsanity.com/paper/2508.06640/) (2025)
- [Evaluating and Correcting Human Annotation Bias in Dynamic Micro-Expression Recognition](https://mlsanity.com/paper/2603.04766/) (2026)
- [Multi-scale multi-modal micro-expression recognition algorithm based on transformer](https://mlsanity.com/paper/2301.02969/) (2023)
- [Hierarchical Space-Time Attention for Micro-Expression Recognition](https://mlsanity.com/paper/2405.03202/) (2024)
- [Temporal and Spatial Feature Fusion Framework for Dynamic Micro Expression Recognition](https://mlsanity.com/paper/2505.16372/) (2025)
- [From Macro to Micro: Boosting micro-expression recognition via pre-training on macro-expression videos](https://mlsanity.com/paper/2405.16451/) (2024)
- [Three-Stream Temporal-Shift Attention Network Based on Self-Knowledge Distillation for Micro-Expression Recognition](https://mlsanity.com/paper/2406.17538/) (2024)
- [A Benchmark for Incremental Micro-expression Recognition](https://mlsanity.com/paper/2501.19111/) (2025)
- [FaceSleuth-R: Adaptive Orientation-Aware Attention for Robust Micro-Expression Recognition](https://mlsanity.com/paper/2506.02695/) (2025)
- [Adaptive Fusion Network with Temporal-Ranked and Motion-Intensity Dynamic Images for Micro-expression Recognition](https://mlsanity.com/paper/2510.09730/) (2025)
- [MEDN: Motion-Emotion Feature Decoupling Network for Micro-Expression Recognition](https://mlsanity.com/paper/2604.17899/) (2026)
- [CDER-SME: A Cross-Device Event-RGB Micro-Expression Dataset under Multi-Level Stress Induction](https://mlsanity.com/paper/2606.20715/) (2026)

## Abstract (arXiv)

Facial micro-expressions (MEs) are involuntary facial motions revealing peoples real feelings and play an important role in the early intervention of mental illness, the national security, and many human-computer interaction systems. However, existing micro-expression datasets are limited and usually pose some challenges for training good classifiers. To model the subtle facial muscle motions, we propose a robust micro-expression recognition (MER) framework, namely muscle motion-guided network (MMNet). Specifically, a continuous attention (CA) block is introduced to focus on modeling local subtle muscle motion patterns with little identity information, which is different from most previous methods that directly extract features from complete video frames with much identity information. Besides, we design a position calibration (PC) module based on the vision transformer. By adding the position embeddings of the face generated by PC module at the end of the two branches, the PC module can help to add position information to facial muscle motion pattern features for the MER. Extensive experiments on three public micro-expression datasets demonstrate that our approach outperforms state-of-the-art methods by a large margin.