# Towards Reading Hidden Emotions: A comparative Study of Spontaneous Micro-expression Spotting and Recognition Methods

arXiv: https://arxiv.org/abs/1511.00423 · HTML: https://mlsanity.com/paper/1511.00423/

## Key facts

- Cited by 37 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Nov 2015.

## Built on by (most cited first, 30 of 37)

- [Video-based Facial Micro-Expression Analysis: A Survey of Datasets, Features and Algorithms](https://mlsanity.com/paper/2201.12728/) (2022)
- [Deep Learning for Micro-expression Recognition: A Survey](https://mlsanity.com/paper/2107.02823/) (2021)
- [Feature refinement: An expression-specific feature learning and fusion method for micro-expression recognition](https://mlsanity.com/paper/2101.04838/) (2021)
- [Short and Long Range Relation Based Spatio-Temporal Transformer for Micro-Expression Recognition](https://mlsanity.com/paper/2112.05851/) (2021)
- [MMNet: Muscle motion-guided network for micro-expression recognition](https://mlsanity.com/paper/2201.05297/) (2022)
- [Feature Representation Learning with Adaptive Displacement Generation and Transformer Fusion for Micro-Expression Recognition](https://mlsanity.com/paper/2304.04420/) (2023)
- [DFME: A New Benchmark for Dynamic Facial Micro-expression Recognition](https://mlsanity.com/paper/2301.00985/) (2023)
- [Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion](https://mlsanity.com/paper/2307.13463/) (2023)
- [MOL: Joint Estimation of Micro-Expression, Optical Flow, and Landmark via Transformer-Graph-Style Convolution](https://mlsanity.com/paper/2506.14511/) (2025)
- [Data Leakage and Evaluation Issues in Micro-Expression Analysis](https://mlsanity.com/paper/2211.11425/) (2022)
- [Geometric Graph Representation with Learnable Graph Structure and Adaptive AU Constraint for Micro-Expression Recognition](https://mlsanity.com/paper/2205.00380/) (2022)
- [Synergistic Spotting and Recognition of Micro-Expression via Temporal State Transition](https://mlsanity.com/paper/2409.09707/) (2024)
- [Facial Expression Analysis and Its Potentials in IoT Systems: A Contemporary Survey](https://mlsanity.com/paper/2412.17616/) (2024)
- [A comparative study on movement feature in different directions for micro-expression recognition](https://mlsanity.com/paper/2102.08068/) (2021)
- [RMES: Real-Time Micro-Expression Spotting Using Phase From Riesz Pyramid](https://mlsanity.com/paper/2305.05523/) (2023)
- [Meta-Auxiliary Learning for Micro-Expression Recognition](https://mlsanity.com/paper/2404.12024/) (2024)
- [Causal-Ex: Causal Graph-based Micro and Macro Expression Spotting](https://mlsanity.com/paper/2503.09098/) (2025)
- [Deep Insights of Learning based Micro Expression Recognition: A Perspective on Promises, Challenges and Research Needs](https://mlsanity.com/paper/2210.04935/) (2022)
- [Prior Information based Decomposition and Reconstruction Learning for Micro-Expression Recognition](https://mlsanity.com/paper/2303.01776/) (2023)
- [FED-PsyAU: Privacy-Preserving Micro-Expression Recognition via Psychological AU Coordination and Dynamic Facial Motion Modeling](https://mlsanity.com/paper/2507.20557/) (2025)
- [Evaluating and Correcting Human Annotation Bias in Dynamic Micro-Expression Recognition](https://mlsanity.com/paper/2603.04766/) (2026)
- [MAC 2026: Advancing Micro-Action Analysis Towards Fine-Grained Understanding](https://mlsanity.com/paper/2607.16284/) (2026)
- [Automatic Micro-Expression Apex Frame Spotting using Local Binary Pattern from Six Intersection Planes](https://mlsanity.com/paper/2104.02149/) (2021)
- [Dynamic Texture Recognition using PDV Hashing and Dictionary Learning on Multi-scale Volume Local Binary Pattern](https://mlsanity.com/paper/2111.12315/) (2021)
- [Multimodal Latent Emotion Recognition from Micro-expression and Physiological Signals](https://mlsanity.com/paper/2308.12156/) (2023)
- [ME-TST+: Micro-expression Analysis via Temporal State Transition with ROI Relationship Awareness](https://mlsanity.com/paper/2508.08082/) (2025)
- [Boosting Micro-Expression Analysis via Prior-Guided Video-Level Regression](https://mlsanity.com/paper/2508.18834/) (2025)
- [Apex-Centered Spatio-Temporal Rank Pooling and Gradient Attention for Micro-Expression Recognition](https://mlsanity.com/paper/2509.00056/) (2025)
- [Micro-Expression Recognition via Fine-Grained Dynamic Perception](https://mlsanity.com/paper/2509.06015/) (2025)
- [A Dynamic 3D Spontaneous Micro-expression Database: Establishment and Evaluation](https://mlsanity.com/paper/2108.00166/) (2021)

## Abstract (arXiv)

Micro-expressions (MEs) are rapid, involuntary facial expressions which reveal emotions that people do not intend to show. Studying MEs is valuable as recognizing them has many important applications, particularly in forensic science and psychotherapy. However, analyzing spontaneous MEs is very challenging due to their short duration and low intensity. Automatic ME analysis includes two tasks: ME spotting and ME recognition. For ME spotting, previous studies have focused on posed rather than spontaneous videos. For ME recognition, the performance of previous studies is low. To address these challenges, we make the following contributions: (i)We propose the first method for spotting spontaneous MEs in long videos (by exploiting feature difference contrast). This method is training free and works on arbitrary unseen videos. (ii)We present an advanced ME recognition framework, which outperforms previous work by a large margin on two challenging spontaneous ME databases (SMIC and CASMEII). (iii)We propose the first automatic ME analysis system (MESR), which can spot and recognize MEs from spontaneous video data. Finally, we show our method outperforms humans in the ME recognition task by a large margin, and achieves comparable performance to humans at the very challenging task of spotting and then recognizing spontaneous MEs.