# SAMM Long Videos: A Spontaneous Facial Micro- and Macro-Expressions Dataset

arXiv: https://arxiv.org/abs/1911.01519 · HTML: https://mlsanity.com/paper/1911.01519/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Nov 2019.

## Built on by (most cited first, 25 of 25)

- [3D-CNN for Facial Micro- and Macro-expression Spotting on Long Video Sequences using Temporal Oriented Reference Frame](https://mlsanity.com/paper/2105.06340/) (2021)
- [Deception Detection and Remote Physiological Monitoring: A Dataset and Baseline Experimental Results](https://mlsanity.com/paper/2106.06583/) (2021)
- [Shallow Optical Flow Three-Stream CNN for Macro- and Micro-Expression Spotting from Long Videos](https://mlsanity.com/paper/2106.06489/) (2021)
- [AU-aware graph convolutional network for Macro- and Micro-expression spotting](https://mlsanity.com/paper/2303.09114/) (2023)
- [Synergistic Spotting and Recognition of Micro-Expression via Temporal State Transition](https://mlsanity.com/paper/2409.09707/) (2024)
- [Weakly-supervised Micro- and Macro-expression Spotting Based on Multi-level Consistency](https://mlsanity.com/paper/2305.02734/) (2023)
- [Multi-Scale Spatio-Temporal Graph Convolutional Network for Facial Expression Spotting](https://mlsanity.com/paper/2403.15994/) (2024)
- [Exploring Timeline Control for Facial Motion Generation](https://mlsanity.com/paper/2505.20861/) (2025)
- [RMES: Real-Time Micro-Expression Spotting Using Phase From Riesz Pyramid](https://mlsanity.com/paper/2305.05523/) (2023)
- [SpotFormer: Multi-Scale Spatio-Temporal Transformer for Facial Expression Spotting](https://mlsanity.com/paper/2407.20799/) (2024)
- [Weak Supervision with Arbitrary Single Frame for Micro- and Macro-expression Spotting](https://mlsanity.com/paper/2403.14240/) (2024)
- [MEGC2025: Micro-Expression Grand Challenge on Spot Then Recognize and Visual Question Answering](https://mlsanity.com/paper/2506.15298/) (2025)
- [Transferring Dual Stochastic Graph Convolutional Network for Facial Micro-expression Recognition](https://mlsanity.com/paper/2203.05208/) (2022)
- [Temporal and Spatial Feature Fusion Framework for Dynamic Micro Expression Recognition](https://mlsanity.com/paper/2505.16372/) (2025)
- [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)
- [Micro-Expression Recognition Based on Attribute Information Embedding and Cross-modal Contrastive Learning](https://mlsanity.com/paper/2205.14643/) (2022)
- [SDFE-LV: A Large-Scale, Multi-Source, and Unconstrained Database for Spotting Dynamic Facial Expressions in Long Videos](https://mlsanity.com/paper/2209.08445/) (2022)
- [PESFormer: Boosting Macro- and Micro-expression Spotting with Direct Timestamp Encoding](https://mlsanity.com/paper/2410.18695/) (2024)
- [AHMSA-Net: Adaptive Hierarchical Multi-Scale Attention Network for Micro-Expression Recognition](https://mlsanity.com/paper/2501.02539/) (2025)
- [End-to-End Facial Expression Detection in Long Videos](https://mlsanity.com/paper/2504.07660/) (2025)
- [Point-Supervised Facial Expression Spotting with Gaussian-Based Instance-Adaptive Intensity Modeling](https://mlsanity.com/paper/2511.16952/) (2025)
- [MEGC2026: Micro-Expression Grand Challenge on Visual Question Answering](https://mlsanity.com/paper/2603.08927/) (2026)
- [MagPlus: Bridging Micro-to-Regular Facial Expressions through Learnable Magnification](https://mlsanity.com/paper/2606.13312/) (2026)
- [AU-Guided Synthetic Video Generation for Micro-Expression Recognition](https://mlsanity.com/paper/2607.10860/) (2026)

## Abstract (arXiv)

With the growth of popularity of facial micro-expressions in recent years, the demand for long videos with micro- and macro-expressions remains high. Extended from SAMM, a micro-expressions dataset released in 2016, this paper presents SAMM Long Videos dataset for spontaneous micro- and macro-expressions recognition and spotting. SAMM Long Videos dataset consists of 147 long videos with 343 macro-expressions and 159 micro-expressions. The dataset is FACS-coded with detailed Action Units (AUs). We compare our dataset with Chinese Academy of Sciences Macro-Expressions and Micro-Expressions (CAS(ME)2) dataset, which is the only available fully annotated dataset with micro- and macro-expressions. Furthermore, we preprocess the long videos using OpenFace, which includes face alignment and detection of facial AUs. We conduct facial expression spotting using this dataset and compare it with the baseline of MEGC III. Our spotting method outperformed the baseline result with F1-score of 0.3299.