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

arXiv 1911.01519 ↗First posted 4 Nov 2019cs.CVcited by 25

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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.

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

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Citing papers per year: 2021: 3; 2022: 3; 2023: 3; 2024: 5; 2025: 8; 2026: 3.

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  1. 20213D-CNN for Facial Micro- and Macro-expression Spotting on Long Video Sequences using Temporal Oriented Reference Framecited by 16
  2. 2021Deception Detection and Remote Physiological Monitoring: A Dataset and Baseline Experimental Resultscited by 16
  3. 2021Shallow Optical Flow Three-Stream CNN for Macro- and Micro-Expression Spotting from Long Videoscited by 14
  4. 2023AU-aware graph convolutional network for Macro- and Micro-expression spottingcited by 9
  5. 2024Synergistic Spotting and Recognition of Micro-Expression via Temporal State Transitioncited by 6
  6. 2023Weakly-supervised Micro- and Macro-expression Spotting Based on Multi-level Consistencycited by 4
  7. 2024Multi-Scale Spatio-Temporal Graph Convolutional Network for Facial Expression Spottingcited by 4
  8. 2025Exploring Timeline Control for Facial Motion Generationcited by 4
  9. 2023RMES: Real-Time Micro-Expression Spotting Using Phase From Riesz Pyramidcited by 3
  10. 2024SpotFormer: Multi-Scale Spatio-Temporal Transformer for Facial Expression Spottingcited by 3
  11. 2024Weak Supervision with Arbitrary Single Frame for Micro- and Macro-expression Spottingcited by 2
  12. 2025MEGC2025: Micro-Expression Grand Challenge on Spot Then Recognize and Visual Question Answeringcited by 2
13 more
  1. 2022Transferring Dual Stochastic Graph Convolutional Network for Facial Micro-expression Recognitioncited by 1
  2. 2025Temporal and Spatial Feature Fusion Framework for Dynamic Micro Expression Recognitioncited by 1
  3. 2025ME-TST+: Micro-expression Analysis via Temporal State Transition with ROI Relationship Awarenesscited by 1
  4. 2025Boosting Micro-Expression Analysis via Prior-Guided Video-Level Regressioncited by 1
  5. 2022Micro-Expression Recognition Based on Attribute Information Embedding and Cross-modal Contrastive Learningcited by 0
  6. 2022SDFE-LV: A Large-Scale, Multi-Source, and Unconstrained Database for Spotting Dynamic Facial Expressions in Long Videoscited by 0
  7. 2024PESFormer: Boosting Macro- and Micro-expression Spotting with Direct Timestamp Encodingcited by 0
  8. 2025AHMSA-Net: Adaptive Hierarchical Multi-Scale Attention Network for Micro-Expression Recognitioncited by 0
  9. 2025End-to-End Facial Expression Detection in Long Videoscited by 0
  10. 2025Point-Supervised Facial Expression Spotting with Gaussian-Based Instance-Adaptive Intensity Modelingcited by 0
  11. 2026MEGC2026: Micro-Expression Grand Challenge on Visual Question Answeringcited by 0
  12. 2026MagPlus: Bridging Micro-to-Regular Facial Expressions through Learnable Magnificationcited by 0
  13. 2026AU-Guided Synthetic Video Generation for Micro-Expression Recognitioncited by 0