# AWESOME-FER

**Repository Path**: wei-hongfei/AWESOME-FER

## Basic Information

- **Project Name**: AWESOME-FER
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-07-25
- **Last Updated**: 2021-09-13

## Categories & Tags

**Categories**: Uncategorized

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## README

# AWESOME-FER

:memo: :high_brightness: Top conferences & Journals focused on Facial expression recognition (FER)/ Facial action unit (FAU)

***
:high_brightness: [Datasets](#datasets)

:high_brightness: [Challenges](#challenges)

:high_brightness: [Related Reviews](#related-reviews)

:high_brightness: [Related Conferences and Journals](#related-conferences-and-journals)

:high_brightness: [Facial Expression Recognition (FER)](#facial-expression-recognition)
 
:high_brightness: [Facial Action Unit Recognition](#facial-action-unit-recognition)

:high_brightness: [Affective Level Estimation](#affective-level-estimation)

## Datasets
- [Jaffe](http://www.kasrl.org/jaffe.html)
- [FER-2013](https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge)
- [MMI Facial Expression Database](https://www.mmifacedb.eu/)
- [Cohn-Kanade Expression Database](http://www.pitt.edu/~emotion/ck-spread.htm)
- [Oulu-CASIA NIR&VIS facial expression database](http://www.cse.oulu.fi/CMV/Downloads/Oulu-CASIA)
- [Multi-PIE](http://www.flintbox.com/public/project/4742/)
- [Binghamton University 3D Facial Expression Database (BU-3DFE)](http://www.cs.binghamton.edu/~lijun/Research/3DFE/3DFE_Analysis.html)
- [Real-world Affective Faces (RAF) Database](http://www.whdeng.cn/RAF/model1.html)
- [AffectNet](http://mohammadmahoor.com/affectnet/)
- [EmotioNet Database](http://cbcsl.ece.ohio-state.edu/dbform_emotionet.html)
- [The Radboud Faces Database (RaFD)](http://www.socsci.ru.nl:8180/RaFD2/RaFD)
- [Aff-Wild data](https://ibug.doc.ic.ac.uk/resources/first-affect-wild-challenge/)
- [A novel database of Children’s Spontaneous Facial Expressions (LIRIS-CSE)](https://childrenfacialexpression.projet.liris.cnrs.fr/)
- [FEAFA: A Well-Annotated Dataset for
 Facial Expression Analysis and 3D Facial Animation](http://www.iiplab.net/feafa/)
- [Facial Expression Research Group Database (FERG-DB)](http://grail.cs.washington.edu/projects/deepexpr/ferg-2d-db.html)
- [Emotions In Context dataset (EMOTIC)](http://sunai.uoc.edu/emotic/)
- [Denver Intensity of Spontaneous Facial Action Database (DISFA)](http://mohammadmahoor.com/disfa/)
- [The MPLab GENKI Database (GENKI-4K)](https://inc.ucsd.edu/mplab/wordpress/index.html%3Fp=398.html)
- [AFFECTIVA-MIT Facial Expression Dataset (AM-FED)](https://www.affectiva.com/facial-expression-dataset-/)
- [The UNBC-McMaster Shoulder Pain Expression
Archive Database (UNBC)](https://ieeexplore.ieee.org/document/5771462)

## Challenges
- [Emotion Recognition in the Wild Challenge (EmotiW) @ ICMI](https://sites.google.com/view/emotiw2018)
- [Group-level happiness intensity recognition @ ICMI](https://sites.google.com/site/emotiw2016/challenge-details)
- [Multimodal Sentiment Analysis Challenge (MuSe) @ ACM MM](https://www.muse-challenge.org/)
- [Audio/Visual Emotion Challenge (AVEC) @ ACM MM](https://sites.google.com/view/avec2019/home?authuser=0)
- [Large Scale Emotion Recognition and Analysis (LERA) @ FG](https://sites.google.com/view/lera2019)
- [Facial Expression Recognition and Analysis Challenge (FERA) @ FG](http://www.fg2017.org/index.php/challenges/)
- [One-Minute Gradual-Emotion Behavior Challenge @ IJCNN](https://www2.informatik.uni-hamburg.de/wtm/OMG-EmotionChallenge/)
- [EmotioNet Challenge](http://cbcsl.ece.ohio-state.edu/EmotionNetChallenge/index.html)
- [Real Versus Fake Expressed Emotions @ ICCV](http://openaccess.thecvf.com/ICCV2017_workshops/ICCV2017_W44.py)
- [Affect-in-the-Wild Challenge @ CVPR](https://ibug.doc.ic.ac.uk/resources/first-affect-wild-challenge/)
- [Affective Behavior Analysis in-the-wild (ABAW) @ FG](https://ibug.doc.ic.ac.uk/resources/fg-2020-competition-affective-behavior-analysis/)
- [EmoPain Challenge: Pain-related Behavior Analysis @ FG](https://mvrjustid.github.io/EmoPainChallenge2020/)

## Related Reviews
- (IEEE Transactions on Affective Computing 20) Deep Facial Expression Recognition: A Survey [[paper](https://arxiv.org/pdf/1804.08348.pdf)]
- (ACM Computing Surveys 19) Facial Expression Analysis under Partial Occlusion: A Survey [[paper](https://arxiv.org/pdf/1802.08784.pdf)]
- (IEEE Transactions on Affective Computing 19) Deep Learning for Human Affect Recognition: Insights and New Developments [[paper](https://ieeexplore.ieee.org/document/8598999)]
- (IEEE Transactions on Affective Computing 18) Survey on Emotional Body Gesture Recognition [[paper](https://ieeexplore.ieee.org/document/8493586)]
- (IEEE Transactions on Affective Computing 17) Automatic Analysis of Facial Actions: A Survey [[paper](https://ieeexplore.ieee.org/document/7990582)]
- (IEEE Transactions on Pattern Analysis and Machine Intelligence 16) Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications[[paper](https://ieeexplore.ieee.org/document/7374704)]
- (IEEE Transactions on Pattern Analysis and Machine Intelligence 15) Automatic Analysis of Facial Affect: A Survey of
Registration, Representation, and Recognition [[paper](https://ieeexplore.ieee.org/document/6940284)]
- (Image and Vision Computing 13) Categorical and dimensional affect analysis in continuous input: Current trends and future directions [[paper](https://www.sciencedirect.com/science/article/pii/S0262885612001084)]
- (FG 11) Emotion representation, analysis and synthesis in continuous space: A survey [[paper](https://ieeexplore.ieee.org/document/5771357)]

## Related Conferences and Journals

### :small_orange_diamond: Conferences 
[CVPR](http://cvpr2019.thecvf.com/),[ICCV](http://iccv2019.thecvf.com/),[ECCV](https://eccv2018.org/),[FG](http://fg2019.org/),[ACM MM](https://www.acmmm.org/2019/),[AAAI](https://aaai.org/Conferences/AAAI-19/),[IJCAI](https://ijcai19.org/),[BMVC](https://bmvc2019.org/),[ACCV](http://accv2020.kyoto/),[WACV](http://wacv19.wacv.net/),[ICMI](http://icmi.acm.org/2019/),[ICPR](https://www.micc.unifi.it/icpr2020/),[ICIP](https://2020.ieeeicip.org/),[ACII](http://acii-conf.org/2019/),[ICB](https://www.icb2019.org/),[BIBM](https://ieeebibm.org/BIBM2019/),[ICASSP](https://2020.ieeeicassp.org/)

### :small_orange_diamond: Journals
[IEEE Transactions on Pattern Analysis and Machine Intelligence](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=34),
[IEEE Transactions on Image Processing](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=83),[Pattern Recognition](https://www.journals.elsevier.com/pattern-recognition),
[IEEE Transactions on Affective Computing](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369),
[Pattern Recognition](https://www.journals.elsevier.com/pattern-recognition),
[International Journal of Computer Vision](https://www.springer.com/journal/11263),
[IEEE Transactions on Systems, Man, and Cybernetics](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221021),
[IEEE Journal of Biomedical and Health Informatic](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221020),
[IEEE Transactions on Human-Machine Systems](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221037),
[Image and Vision Computing](https://www.journals.elsevier.com/image-and-vision-computing),
[Computer Vision and Image Understanding](https://www.journals.elsevier.com/computer-vision-and-image-understanding),
[IEEE Transactions on Circuits and Systems for Video Technology](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=76),
[IEEE Transactions on Cognitive and Developmental Systems](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7274989),
[IEEE Transactions on Cybernetics](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221036),
[IEEE Transactions on Multimedia](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6046),
[IEEE Access](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639),
[IEEE-ACM Transactions on Computational Biology and Bioinformatics](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8857),
[Neurocomputing](https://www.journals.elsevier.com/neurocomputing),
[IEEE Transactions on Biometrics, Behavior, and Identity Science](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8423754),
[Pattern Recognition Letters](https://www.journals.elsevier.com/pattern-recognition-letters)
[IEEE Transactions on Biomedical Engineering](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=10)

### :small_orange_diamond: Workshops
- IJCAI Affective Computing Workshop (AffComp) [[2019](http://kdd.cs.ksu.edu/KDD/Workshops/IJCAI-2019-AffComp/)],[[2018](http://kdd.cs.ksu.edu/Workshops/IJCAI-2018-AffComp/)],[[2017](http://kdd.cs.ksu.edu/Workshops/IJCAI-2017-AffComp/)]
- AAAI Workshop on Affective Content Analysis (AffCon) [[2020](https://sites.google.com/view/affcon2020)],[[2019](https://sites.google.com/view/affcon2019/home)],[[2018](https://sites.google.com/view/affcon18/home)]
- CVPR Workshop on Deep Affective Learning and Context Modelling (DAL-COM) [[2017](https://sites.google.com/site/dalcom2017cvpr/home)]

## Facial Expression Recognition

### :small_orange_diamond: IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
- (2021) Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition [[paper](https://arxiv.org/pdf/2104.05160.pdf)]
- (2021) Affective Processes: Stochastic Modelling of Temporal Context for Emotion and Facial Expression Recognition [[paper](https://arxiv.org/pdf/2103.13372.pdf)]
- (2021) Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition [[paper](https://arxiv.org/pdf/2104.00232.pdf)]
- (2020) Label Distribution Learning on Auxiliary Label Space Graphs
for Facial Expression Recognition [[paper](http://palm.seu.edu.cn/xgeng/files/cvpr20.pdf)]
- (2020) Suppressing Uncertainties for Large-Scale Facial Expression Recognition [[paper](https://arxiv.org/pdf/2002.10392.pdf)]
- (2020) EmotiCon: Context-Aware Multimodal Emotion Recognition using Frege’s
Principle [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Mittal_EmotiCon_Context-Aware_Multimodal_Emotion_Recognition_Using_Freges_Principle_CVPR_2020_paper.pdf)]
- (2020) Cascade EF-GAN: Progressive Facial Expression Editing with Local Focuses [[paper](https://www.researchgate.net/publication/339898835_Cascade_EF-GAN_Progressive_Facial_Expression_Editing_with_Local_Focuses)]
- (2019) A Compact Embedding for Facial Expression Similarity [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Vemulapalli_A_Compact_Embedding_for_Facial_Expression_Similarity_CVPR_2019_paper.pdf)]
- (2019) Facial Emotion Distribution Learning by Exploiting Low-Rank Label Correlations Locally [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Jia_Facial_Emotion_Distribution_Learning_by_Exploiting_Low-Rank_Label_Correlations_Locally_CVPR_2019_paper.pdf)]
- (2019) Learning to Regress 3D Face Shape and Expression
from an Image without 3D Supervision [[paper](https://arxiv.org/pdf/1905.06817.pdf)]][[code](https://github.com/soubhiksanyal/RingNet)]
- (2018) Facial Expression Recognition by De-expression Residue Learning [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Facial_Expression_Recognition_CVPR_2018_paper.pdf)][:dizzy::dizzy::dizzy:]
- (2018) Joint Pose and Expression Modeling for Facial Expression Recognition [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Joint_Pose_and_CVPR_2018_paper.pdf)],[[code](https://github.com/FFZhang1231/Facial-expression-recognition)][:dizzy::dizzy:]
- (2018) 4DFAB: A Large Scale 4D Database for Facial Expression Analysis and Biometric Applications [[paper](https://ibug.doc.ic.ac.uk/media/uploads/documents/3299.pdf)]][:dizzy:]
- (2017) Reliable Crowdsourcing and Deep Locality-Preserving Learning for Expression
Recognition in the Wild [[paper](http://openaccess.thecvf.com/content_cvpr_2017/papers/Li_Reliable_Crowdsourcing_and_CVPR_2017_paper.pdf)][:dizzy:]
- (2017) Emotion Recognition in Context [[paper](http://openaccess.thecvf.com/content_cvpr_2017/papers/Kosti_Emotion_Recognition_in_CVPR_2017_paper.pdf)][:dizzy:]
- (2016) LOMo: Latent Ordinal Model for Facial Analysis in Videos [[paper](http://www.grvsharma.com/hpresources/lomo_cvpr16_arxiv.pdf)][:dizzy:]
- (2016) Facial Expression Intensity Estimation Using Ordinal Information [[paper](http://openaccess.thecvf.com/content_cvpr_2016/papers/Zhao_Facial_Expression_Intensity_CVPR_2016_paper.pdf)],[[Supplementary](http://openaccess.thecvf.com/content_cvpr_2016/supplemental/Zhao_Facial_Expression_Intensity_2016_CVPR_supplemental.pdf)][:dizzy::dizzy:]
- (2016) EmotioNet: An accurate, real-time algorithm for the automatic annotation of a
million facial expressions in the wild [[paper](http://openaccess.thecvf.com/content_cvpr_2016/papers/Benitez-Quiroz_EmotioNet_An_Accurate_CVPR_2016_paper.pdf)],[[Supplementary](http://openaccess.thecvf.com/content_cvpr_2016/supplemental/Benitez-Quiroz_EmotioNet_An_Accurate_2016_CVPR_supplemental.pdf)][:dizzy:]
- (2016) Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis [[paper](http://openaccess.thecvf.com/content_cvpr_2016/papers/Zhang_Multimodal_Spontaneous_Emotion_CVPR_2016_paper.pdf)][:dizzy:]
- (2014) Learning Expressionlets on Spatio-Temporal Manifold for Dynamic Facial
Expression Recognition [[paper](https://www.cv-foundation.org/openaccess/content_cvpr_2014/papers/Liu_Learning_Expressionlets_on_2014_CVPR_paper.pdf)][:dizzy::dizzy:]
- (2014) Facial Expression Recognition via a Boosted Deep Belief Network [[paper](http://openaccess.thecvf.com/content_cvpr_2014/papers/Liu_Facial_Expression_Recognition_2014_CVPR_paper.pdf)][:dizzy:]
- (2013) Capturing Complex Spatio-Temporal Relations among Facial
Muscles for Facial Expression Recognition [[paper](http://f4k.dieei.unict.it/proceedings/CVPR13/data/papers/4989d422.pdf)][:dizzy:]

### :small_orange_diamond: International Conference on Computer Vision (ICCV)
- (2019) Context-Aware Emotion Recognition Networks [[paper](https://arxiv.org/pdf/1908.05913.pdf)]
- (2019) Attention-Aware Polarity Sensitive Embedding for Affective Image Retrieval [[paper]()]
- (2019) Zero-Shot Emotion Recognition via Affective Structural Embedding [[paper]()]
- (2017) A Novel Space-Time Representation on the Positive Semidefinite Cone
for Facial Expression Recognition [[paper](https://arxiv.org/pdf/1707.06440.pdf)][:dizzy:]
- (2015) Joint Fine-Tuning in Deep Neural Networks
for Facial Expression Recognition [[paper](https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Jung_Joint_Fine-Tuning_in_ICCV_2015_paper.pdf)][:dizzy::dizzy::dizzy:]
- (2015) Pairwise Conditional Random Forests for Facial Expression Recognition [[paper](http://openaccess.thecvf.com/content_iccv_2015/papers/Dapogny_Pairwise_Conditional_Random_ICCV_2015_paper.pdf)][:dizzy:]

### :small_orange_diamond: European Conference on Computer Vision (ECCV)
- (2018) Facial Expression Recognition with Inconsistently Annotated Datasets [[paper](https://eccv2018.org/openaccess/content_ECCV_2018/papers/Jiabei_Zeng_Facial_Expression_Recognition_ECCV_2018_paper.pdf)]
- (2018) Contemplating Visual Emotions: Understanding and Overcoming Dataset Bias [[paper](https://arxiv.org/pdf/1808.02212.pdf)]
- (2018) Deep Multi-Task Learning to Recognise Subtle
Facial Expressions of Mental States [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Guosheng_Hu_Deep_Multi-Task_Learning_ECCV_2018_paper.pdf)]
- (2016) Peak-Piloted Deep Network for Facial Expression
Recognition [[paper](https://arxiv.org/pdf/1607.06997.pdf)][:dizzy::dizzy::dizzy:]

### :small_orange_diamond: Association for the Advance of Artificial Intelligence (AAAI)
- (2021) Robust Lightweight Facial Expression Recognition Network with Label Distribution Training [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/16465)],[[code](https://github.com/zengqunzhao/EfficientFace)]
- (2020) Efficient facial feature learning with wide ensemble-based convolutional neural networks [[paper](https://www2.informatik.uni-hamburg.de/wtm/publications/2020/SMW20/SMW20.pdf)]
- (2020) MIMAMO Net: Integrating Micro- and Macro-motion for Video Emotion
Recognition [[paper](https://arxiv.org/pdf/1911.09784.pdf)]
- (2020) M3ER: Multiplicative Multimodal Emotion Recognition Using Facial, Textual, and Speech Cues [[paper](https://arxiv.org/pdf/1911.05659.pdf)]
- (2020) An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos [[paper](https://arxiv.org/abs/2003.00832)]
- (2019) Mode Variational LSTM Robust to Unseen Modes of Variation: Application to
Facial Expression Recognition [[paper](https://arxiv.org/pdf/1811.06937.pdf)]
- (2019) Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation [[paper](https://arxiv.org/pdf/1808.02992.pdf)]
- (2019) CycleEmotionGAN: Emotional Semantic Consistency Preserved CycleGAN for Adapting
Image Emotions [[paper](https://www.aaai.org/ojs/index.php/AAAI/article/view/4110)]
- (2018) ExprGAN: Facial Expression Editing with Controllable Expression Intensity [[paper](https://arxiv.org/pdf/1709.03842.pdf)],[[code](https://github.com/HuiDingUMD/ExprGAN)][:dizzy:]
- (2018) Learning Spatio-temporal Features with Partial Expression Sequences for on-the-Fly Prediction [[paper](https://arxiv.org/pdf/1711.10914.pdf)]][:dizzy:]

### :small_orange_diamond: ACM International Conference on Multimedia (ACM MM)
- (2020) IExpressNet: Facial Expression Recognition with Incremental Classes [[paper](https://dl.acm.org/doi/abs/10.1145/3394171.3413718)]
- (2020) Occluded Facial Expression Recognition with Step-Wise Assistance from Unpaired Non-Occluded Images [[paper](https://dl.acm.org/doi/abs/10.1145/3394171.3413773)]
- (2020) Uncertainty-aware Cross-dataset Facial Expression Recognition via Regularized Conditional Alignment [[paper](https://dl.acm.org/doi/abs/10.1145/3394171.3413515)]
- (2020) R-FENet: A Region-based Facial Expression Recognition Method Inspired by Semantic Information of Action Units [[paper](https://dl.acm.org/doi/abs/10.1145/3422852.3423482)]
- (2020) A Novel Graph-TCN with a Graph Structured Representation for Micro-expression Recognition [[paper](https://dl.acm.org/doi/abs/10.1145/3394171.3413714)]
- (2020) DFEW: A Large-Scale Database for Recognizing Dynamic Facial
Expressions in the Wild [[paper](https://arxiv.org/pdf/2008.05924.pdf)]
- (2020) Adversarial Graph Representation Adaptation
for Cross-Domain Facial Expression Recognition [[paper](https://arxiv.org/pdf/2008.00859.pdf)],[[code](https://github.com/HCPLab-SYSU/CD-FER-Benchmark)]
- (2019) Occluded Facial Expression Recognition Enhanced through Privileged Information [[paper](https://dl.acm.org/citation.cfm?doid=3343031.3351049)]
- (2019) Identity- and Pose-Robust Facial Expression Recognition through Adversarial Feature Learning [[paper](https://dl.acm.org/citation.cfm?id=3350872)]
- (2019) Comp-GAN: Compositional Generative Adversarial Network in Synthesizing and Recognizing Facial Expression [[paper](https://dl.acm.org/citation.cfm?id=3351032)]
- (2019) PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion Regression [[paper](https://arxiv.org/abs/1909.05693)]
- (2018) Fast and Light Manifold CNN based 3D Facial Expression Recognition across Pose Variations [[paper](https://dl.acm.org/citation.cfm?id=3240568)]
- (2018) Facial Expression Recognition in the Wild: A Cycle-Consistent Adversarial Attention Transfer Approach [[paper](https://dl.acm.org/citation.cfm?id=3240574)]
- (2018) Facial Expression Recognition Enhanced by Thermal Images through Adversarial Learning [[paper](https://dl.acm.org/citation.cfm?id=3240608)]
- (2018) Geometry Guided Adversarial Facial Expression Synthesis [[paper](https://arxiv.org/pdf/1712.03474.pdf)]
- (2018) Conditional Expression Synthesis with Face Parsing Transformation [[paper](https://dl.acm.org/citation.cfm?id=3240647)]
- (2017) Learning a Target Sample Re-Generator for Cross-Database
Micro-Expression Recognition [[paper](https://arxiv.org/pdf/1707.08645.pdf)]

### :small_orange_diamond: International Joint Conference on Artificial Intelligence (IJCAI)
- (2020) Weakly Supervised Local-Global Relation Network
for Facial Expression Recognition [[paper](https://www.ijcai.org/Proceedings/2020/0145.pdf)]
- (2018) Personality-Aware Personalized Emotion Recognition from Physiological Signals [[paper](https://www.ijcai.org/proceedings/2018/0230.pdf)]
- (2017) Approximating Discrete Probability Distribution of Image Emotions by
Multi-Modal Features Fusion [[paper](https://www.ijcai.org/proceedings/2017/0651.pdf)]
- (2017) Dependency Exploitation: A Unified CNN-RNN Approach for
Visual Emotion Recognition [[paper](https://www.ijcai.org/proceedings/2017/0503.pdf)]
- (2017) Joint Image Emotion Classification and Distribution Learning
via Deep Convolutional Neural Network [[paper](https://www.ijcai.org/proceedings/2017/0456.pdf)]
- (2016) Multi-View Exclusive Unsupervised Dimension Reduction
for Video-Based Facial Expression Recognition [[paper](https://www.ijcai.org/Proceedings/16/Papers/316.pdf)]

### :small_orange_diamond: International Conference on Machine Learning (ICML)
- （2019）A Personalized Affective Memory Model for Improving Emotion Recognition [[paper](https://arxiv.org/pdf/1904.12632.pdf)]

### :small_orange_diamond: British Machine Vision Conference (BMVC)
- (2019) Annealed Label Transfer for Face Expression Recognition [[paper](https://bmvc2019.org/wp-content/uploads/papers/0321-paper.pdf)]
- (2019) Automatic 4D Facial Expression Recognition via Collaborative Cross-domain Dynamic Image Network [[paper](https://bmvc2019.org/wp-content/uploads/papers/0729-paper.pdf)]
- (2019) An Unsupervised Subspace Ranking Method for Continuous Emotions in Face Images [[paper](https://bmvc2019.org/wp-content/uploads/papers/0831-paper.pdf)]
- (2018) Feature Selection Mechanism in CNNs for Facial Expression Recognition [[paper](http://bmvc2018.org/contents/workshops/iahfar2018/0011.pdf)]

### :small_orange_diamond: IEEE Winter Conference on Applications of Computer Vision (WACV)
- (2019) Graph Neural Networks for Image Understanding Based on Multiple Cues:
Group Emotion Recognition and Event Recognition as Use Cases [[paper](https://arxiv.org/pdf/1909.12911.pdf)]
- (2018) Group Affect Prediction Using Multimodal Distributions [[paper](https://arxiv.org/pdf/1710.01216.pdf)]
- (2016) Going Deeper in Facial Expression Recognition using Deep Neural Networks [[paper](https://arxiv.org/pdf/1511.04110.pdf)][:dizzy:]

### :small_orange_diamond: ACM International Conference on Multimodal Interaction (ICMI)
- (2018) Multi-Feature Based Emotion Recognition for Video Clips [[paper](http://delivery.acm.org/10.1145/3270000/3264989/p630-liu.pdf?ip=118.140.125.72&id=3264989&acc=OA&key=4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E65B561F191013DD0&__acm__=1545619250_535c23ee84805ca9482eaf3dc8bc1590)]
- (2018) Video-based Emotion Recognition Using Deeply-Supervised Neural Networks [[paper](https://dl.acm.org/citation.cfm?id=3264978)]
- (2018) Multiple Spatio-temporal Feature Learning for Video-based Emotion Recognition in the Wild [[paper](https://dl.acm.org/citation.cfm?id=3264992)]
- (2018) An Occam’s Razor View on Learning Audiovisual Emotion
Recognition with Small Training Sets [[paper](https://arxiv.org/pdf/1808.02668.pdf)]
- (2018) Group-Level Emotion Recognition Using Hybrid Deep Models Based on Faces, Scenes, Skeletons and Visual Attentions [[paper](https://dl.acm.org/citation.cfm?id=3264990)]
- (2018) Cascade Attention Networks For Group Emotion Recognition with Face, Body and Image Cues [[paper](https://dl.acm.org/citation.cfm?id=3264991)]
- (2018) Group-Level Emotion Recognition using Deep Models with A Four-stream Hybrid Network [[paper](https://dl.acm.org/citation.cfm?id=3264987)]
- (2018) An Attention Model for group-level emotion recognition[[paper](https://arxiv.org/abs/1807.03380)]
- (2017) Learning supervised scoring ensemble for emotion recognition in the wild [[paper](https://dl.acm.org/citation.cfm?id=3143009)]
- (2017) Convolutional neural networks pretrained on large face recognition datasets for emotion classification from video [[paper](https://arxiv.org/abs/1711.04598)]
- (2017) Temporal Multimodal Fusion for Video Emotion Classification in the Wild [[paper](https://arxiv.org/pdf/1709.07200.pdf)]
- (2017) Emotion recognition with multimodal features and temporal models [[paper](https://dl.acm.org/citation.cfm?doid=3136755.3143016)]
- (2017) Audio-visual emotion recognition using deep transfer learning and multiple temporal models [[paper](https://dl.acm.org/citation.cfm?doid=3136755.3143012)]
- (2017) Cross-Modality Interaction between EEG Signals and Facial
Expression [[paper](https://dl.acm.org/citation.cfm?id=3137034)][:dizzy:]

### :small_orange_diamond: IEEE International Conference on Automatic Face & Gesture Recognition (FG)
- (2020) The FaceChannel: A Light-weight Deep Neural Network for Facial
Expression Recognition [[paper](https://arxiv.org/abs/2004.08195)]
- (2020) CLIFER: Continual Learning with Imagination for Facial Expression Recognition [[paper](https://www.computer.org/csdl/proceedings-article/fg/2020/307900a693/1kecIRr1grK)]
- (2020) Real-time Facial Expression Recognition “In The Wild” by
Disentangling 3D Expression from Identity [[paper](https://arxiv.org/pdf/2005.05509.pdf)]
- (2019) Discriminative Attention-based Convolutional Neural Network for 3D Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8756524)]
- (2019) GF-CapsNet: Using Gabor Jet and Capsule Networks for Facial Age, Gender, and Expression Recognition [[paper](https://ieeexplore.ieee.org/document/8756552)]
- (2019) G2-VER: Geometry Guided Model Ensemble for Video-based Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8756600)]
- (2019) A Graph-Structured Representation with BRNN for Static-based Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8756615)]
- (2019) AFAR: A Deep Learning Based Tool for Automated Facial Affect Recognition [[paper](https://ieeexplore.ieee.org/document/8756623)]
- (2019) Face and Emotion Recognition with Neural Networks on Mobile Devices: Practical Implementation on Different Platforms [[paper](https://ieeexplore.ieee.org/document/8756562)]
- (2019) Hierarchical Group-level Emotion Recognition in the Wild [[paper](https://ieeexplore.ieee.org/document/8756573)]
- (2019) Bounded Residual Gradient Networks (BReG-Net) for Facial Affect
Computing [[paper](https://arxiv.org/pdf/1903.02110.pdf)]
- (2019) Generalizing to unseen head poses in facial expression recognition and action unit intensity estimation [[paper](https://ieeexplore.ieee.org/document/8756596)]
- (2018) Facial Expression Grounded Conversational Dialogue Generation[[paper](https://ieeexplore.ieee.org/document/8373852)]
- (2018) Island Loss for Learning Discriminative Features in Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/document/8373844)]
- (2018) Multi-Channel Pose-Aware Convolution Neural Networks for Multi-View Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/document/8373867)][:dizzy::dizzy::dizzy:]
- (2018) Automatic 4D Facial Expression Recognition using Dynamic
Geometrical Image Network [[paper](https://ieeexplore.ieee.org/document/8373807)][:dizzy:]
- (2018) ExpNet: Landmark-Free, Deep, 3D Facial Expressions [[paper](https://ieeexplore.ieee.org/document/8373820)][[code](https://github.com/fengju514/Expression-Net)][:dizzy:]
- (2018) Perceptual Facial Expression Representation [[paper](https://ieeexplore.ieee.org/document/8373828)][:dizzy:]
- (2018) Emotion-Preserving Representation Learning via Generative Adversarial Network
for Multi-view Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/document/8373839)][:dizzy::dizzy:]
- (2018) Spotting the Details: The Various Facets of Facial Expressions [[paper](https://ieeexplore.ieee.org/document/8373842)][:dizzy:]
- (2018) Identity-Adaptive Facial Expression Recognition Through Expression Regeneration Using Conditional Generative Adversarial Networks [[paper](https://ieeexplore.ieee.org/document/8373843)][:dizzy::dizzy::dizzy:]
- (2018) Hand-crafted Feature Guided Deep Learning for Facial Expression
Recognition [[paper](https://ieeexplore.ieee.org/document/8373861)][:dizzy::dizzy:]
- (2018) Accurate Facial Parts Localization and Deep Learning for 3D Facial Expression
Recognition [[paper](https://ieeexplore.ieee.org/document/8373868)][:dizzy:]
- (2018) Changes in Facial Expression as Biometric: A
Database and Benchmarks of Identification [[paper](https://ieeexplore.ieee.org/document/8373891)][:dizzy:]
- (2018) LTP-ML : Micro-Expression Detection by Recognition of Local temporal Pattern of Facial Movements [[paper](https://ieeexplore.ieee.org/document/8373893)][:dizzy:]
- (2018) From Macro to Micro Expression Recognition: Deep Learning on Small Datasets
Using Transfer Learning  [[paper](https://ieeexplore.ieee.org/document/8373896)][:dizzy:]
- (2018) Unsupervised Domain Adaptation with Regularized Optimal Transport
for Multimodal 2D+3D Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/document/8373808)][:dizzy::dizzy:]
- (2017) Accurate Facial Parts Localization and Deep Learning for 3D Facial
Expression Recognition [[paper](https://arxiv.org/pdf/1803.05846.pdf)][:dizzy:]
- (2017) FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for
Expression Recognition [[paper](https://arxiv.org/pdf/1609.06591.pdf)][:dizzy::dizzy:]
- (2017) Deep generative-contrastive networks for facial expression recognition [[paper](https://arxiv.org/pdf/1703.07140.pdf)][:dizzy::dizzy::dizzy:]
- (2017) Identity-Aware Convolutional Neural Network for Facial Expression
Recognition [[paper](https://cse.sc.edu/~mengz/papers/FG2017.pdf)][:dizzy::dizzy::dizzy:]
- (2017) (workshop) Spatio-Temporal Facial Expression Recognition Using Convolutional
Neural Networks and Conditional Random Fields [[paper](https://arxiv.org/pdf/1703.06995.pdf)][:dizzy:]
- (2017) Head Pose and Expression Transfer using Facial Status Score [[paper](https://ieeexplore.ieee.org/document/7961793)][:dizzy:]
- (2017) Sayette Group Formation Task (GFT)
Spontaneous Facial Expression Database [[paper](https://ieeexplore.ieee.org/document/7961794)][:dizzy::dizzy:]
- (2017) Curriculum Learning for Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/document/7961783)][:dizzy:]
- (2017) Implicit Media Tagging and Affect Prediction from RGB-D video of
spontaneous facial expressions [[paper](https://ieeexplore.ieee.org/document/7961813)][:dizzy::dizzy:]
- (2015) Pairwise Linear Regression: An Efficient and Fast Multi-view Facial
Expression Recognition [[paper](https://ieeexplore.ieee.org/document/7163101)][:dizzy:]

### :small_orange_diamond: IEEE International Conference on Image Processing (ICIP)
- (2019) Frame attention networks for facial expression recognition in videos [[paper](https://arxiv.org/pdf/1907.00193.pdf)]
- (2019) Outlier-Suppressed Triplet Loss with Adaptive Class-Aware Margins for Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8802918)]
- (2019) Facial Expression Recognition Using Adaptive Robust Local Complete Pattern [[paper](https://ieeexplore.ieee.org/abstract/document/8802911)]
- (2019) Dual-stream Shallow Networks for Facial Micro-expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8802965)]
- (2019) Disentangled Feature Based Adversarial Learning for Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8802941)]
- (2019) Edge-Computing Convolutional Neural Network with Homography-Augmented Data for Facial Emotion Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8803675)]

### :small_orange_diamond: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
- (2019) Facial Micro-Expression Spotting and Recognition using Time Contrasted Feature with Visual Memory [[paper](https://arxiv.org/abs/1902.03514)]

###  :small_orange_diamond: IEEE International Conference on Multimedia and Expo (ICME)
- (2019) Context-Aware Affective Graph Reasoning for Emotion Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8784981)]
- (2019) Pooling Map Adaptation in Convolutional Neural Network for Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8785044)]

### :small_orange_diamond: IEEE Transactions on Affective Computing
- (2020) STCAM: Spatial-Temporal and Channel Attention Module for Dynamic Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/9209166)]
- (2020) Phase Space Reconstruction Driven Spatio-Temporal Feature Learning for Dynamic Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/document/9134869)]
- (2020) Facial Expression Recognition with Deeply-Supervised Attention Network [[paper](https://ieeexplore.ieee.org/document/9075283)]
- (2019) On-the-Fly Facial Expression Prediction using LSTM Encoded Appearance-Suppressed Dynamics [[paper](https://ieeexplore.ieee.org/abstract/document/8922646)] 
- (2019) Dynamic Pose-Robust Facial Expression Recognition by Multi-View Pairwise Conditional Random Forests [[paper](https://ieeexplore.ieee.org/document/7934067)]
- (2019) Multi-Velocity Neural Networks for Facial Expression Recognition in Videos [[paper](https://ieeexplore.ieee.org/document/7942120)]
- (2018) Heterogeneous Knowledge Transfer
in Video Emotion Recognition,
Attribution and Summarization [[paper](https://ieeexplore.ieee.org/document/7723914)][:dizzy::dizzy::dizzy:]
- (2018) Emotion Recognition in Simulated Social Interactions [[paper](https://ieeexplore.ieee.org/document/8319988)]
- (2018) Co-clustering to reveal salient facial features for expression recognition[[paper](https://ieeexplore.ieee.org/document/8186192)]
- (2018) Facial Expression Recognition with Identity and Emotion Joint Learning [[paper](https://ieeexplore.ieee.org/document/8528894)]
- (2018) Unsupervised adaptation of a person-specific
manifold of facial expressions [[paper](https://ieeexplore.ieee.org/document/8294217)][:dizzy::dizzy::dizzy:]
- (2018) Multi-velocity neural networks for facial
expression recognition in videos [[paper](https://ieeexplore.ieee.org/document/7942120)][:dizzy::dizzy::dizzy:]
- (2018) Multi-Objective based Spatio-Temporal
Feature Representation Learning Robust to
Expression Intensity Variations for Facial
Expression Recognition [[paper](https://ieeexplore.ieee.org/document/7904596)]
- (2018) Visually Interpretable Representation Learning for
Depression Recognition from Facial Images [[paper](https://ieeexplore.ieee.org/document/8344107)][:dizzy::dizzy::dizzy::dizzy:]
- (2018) Facial Expression Recognition in Video
with Multiple Feature Fusion [[paper](https://ieeexplore.ieee.org/document/7518582)][:dizzy::dizzy:]
- (2018) The Indian Spontaneous Expression Database for Emotion Recognition[[paper](https://ieeexplore.ieee.org/document/7320978)]
- (2018) Cross-Domain Color Facial Expression Recognition Using Transductive Transfer Subspace Learning [[paper](https://ieeexplore.ieee.org/document/7465718)][:dizzy:]

### :small_orange_diamond: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- (2019) Sparse Coding of Shape Trajectories for Facial Expression and Action Recognition [[paper](https://ieeexplore.ieee.org/document/8787885)]
- (2017) Selective Transfer Machine for Personalized
Facial Expression Analysis [[paper](https://ieeexplore.ieee.org/document/7442563)]

### :small_orange_diamond: International Journal of Computer Vision (IJCV)
- (2020) Deep Neural Network Augmentation: Generating Faces for Affect
Analysis [[paper](https://ibug.doc.ic.ac.uk/media/uploads/documents/kollias2020_article_deepneuralnetworkaugmentationg.pdf)]
- (2019) Deep affect prediction in-the-wild: Aff-wild database and challenge, deep architectures, and beyond [[paper](https://link.springer.com/article/10.1007/s11263-019-01158-4)]
- (2019) Blended Emotion in-the-Wild: Multi-label Facial Expression Recognition Using Crowdsourced Annotations and Deep Locality Feature Learning [[paper](https://link.springer.com/article/10.1007/s11263-018-1131-1)]

### :small_orange_diamond: IEEE Transactions on Image Processing (TIP)
- (2021) Learning Deep Global Multi-scale and Local Attention Features for Facial Expression Recognition in the Wild [[paper](https://doi.org/10.1109/TIP.2021.3093397)],[[code](https://github.com/zengqunzhao/MA-Net)]
- (2020) Facial Expression Recognition in Videos 
using Dynamic Kernels [[paper](https://ieeexplore.ieee.org/abstract/document/9153096)]
- (2020) Multi-modal Recurrent Attention Networks for Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/9102419)]
- (2020) A Unified Deep Model for Joint Facial Expression Recognition, Face Synthesis, and Face Alignment [[paper](https://ieeexplore.ieee.org/document/9090326)]
- (2020) Geometry Guided Pose-Invariant Facial
Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8995782)]
- (2018) Occlusion aware facial expression recognition using
CNN with attention mechanism [[paper](https://ieeexplore.ieee.org/document/8576656)]
- (2018) Domain Regeneration for Cross-Database
Micro-Expression Recognition [[paper](https://ieeexplore.ieee.org/document/8268553)][:dizzy:]
- (2017) Facial Expression Recognition Based on Deep
Evolutional Spatial-Temporal Networks [[paper](https://ieeexplore.ieee.org/document/7890464)]
- (2013) Simultaneous Facial Feature Tracking and Facial Expression Recognition [[paper](https://www.researchgate.net/publication/236080803_Simultaneous_Facial_Feature_Tracking_and_Facial_Expression_Recognition)]
- (2005) Active and Dynamic Information Fusion
for Facial Expression Understanding
from Image Sequences [[paper](https://ieeexplore.ieee.org/document/1407874)]

### :small_orange_diamond: Pattern Recognition (PR)
- (2019) Deep multi-path convolutional neural network joint with salient
region attention for facial expression recognition [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320319301268)][:dizzy::dizzy::dizzy::dizzy:]
- (2018) Conditional convolution neural network enhanced random forest for
facial expression recognition [[paper](http://covis.cse.unt.edu/papers/2018Liu.pdf)]
- (2018) Collaborative discriminative multi-metric learning for facial expression recognition in video [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320317300948)]
- (2015) Multimodal learning for facial expression recognition [[paper](https://www.sciencedirect.com/science/article/abs/pii/S003132031500151X)]
- (2014) Facial expression recognition in dynamic sequences:
An integrated approach [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320313003956)]

### :small_orange_diamond: Neurocomputing
- (2019) Semi-supervised facial expression recognition using reduced spatial features and Deep Belief Networks [[paper](https://www.sciencedirect.com/science/article/pii/S0925231219311579)]
- (2019) Three Convolutional Neural Network Models for Facial Expression Recognition in the Wild [[paper](https://www.sciencedirect.com/science/article/pii/S0925231219306137)]
- (2019) Cross-domain facial expression recognition via an intra-category
common feature and inter-category Distinction feature fusion network [[paper](https://www.sciencedirect.com/science/article/pii/S0925231218314929)]
- (2018) Facial expression intensity estimation using Siamese and triplet
networks [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0925231218307926)]
- (2018) A visual attention based ROI detection method for facial expression
recognition [[paper](https://www.sciencedirect.com/science/article/pii/S0925231218303266)]
- (2018) Spatio-temporal convolutional features with nested LSTM for facial
expression recognition [[paper](https://www.sciencedirect.com/science/article/pii/S0925231218308634)][:dizzy::dizzy::dizzy::dizzy:]
- (2017) Emotion-modulated attention improves expression recognition: A deep learning model [[paper](https://www.sciencedirect.com/science/article/pii/S0925231217304551)]
- (2017) An efficient unconstrained facial expression recognition algorithm
based on Stack Binarized Auto-encoders and Binarized Neural
Networks [[paper](https://www.sciencedirect.com/science/article/pii/S0925231217311785)]
- (2016) Transfer subspace learning for cross-dataset facial expression recognition [[paper](https://www.sciencedirect.com/science/article/pii/S0925231216304623)][:dizzy:]
- (2016) A new descriptor of gradients Self-Similarity for smile detection
in unconstrained scenarios [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0925231215014812)]

### :small_orange_diamond: IEEE Transactions on Multimedia
- (2020) Orthogonalization-Guided Feature Fusion Network for Multimodal 2D+3D Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/9115253)]
- (2019) Joint Deep Learning of Facial Expression Synthesis and Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8943107)]
- (2019) Facial Expression Recognition Using Hierarchical Features With Deep Comprehensive Multipatches Aggregation Convolutional Neural Networks [[paper](https://ieeexplore.ieee.org/document/8371638)]
- (2018) MixedEmotions: An Open-Source Toolbox for
Multimodal Emotion Analysis [[paper](https://ieeexplore.ieee.org/document/8269329)]
- (2018) Multimodal Framework for Analyzing the Affect of a Group of People [[paper](https://ieeexplore.ieee.org/abstract/document/8323249)]
- (2016) A Deep Neural Network-Driven Feature Learning Method for Multi-view
Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/document/7530823)][:dizzy:]

### :small_orange_diamond: IEEE Transactions on Circuits and Systems for Video Technology 
- (2020) Facial Expression Recognition with Two-branch Disentangled Generative Adversarial Network [[paper](https://ieeexplore.ieee.org/abstract/document/9197663)]
- (2018) Learning Affective Features With a Hybrid Deep Model for Audio–Visual Emotion Recognition [[paper](https://ieeexplore.ieee.org/document/7956190)]
- (2018) Mixture Statistic Metric Learning for Robust Human Action and Expression Recognition [[paper](https://ieeexplore.ieee.org/abstract/document/8103056)]

### :small_orange_diamond: IEEE Transactions on Cognitive and Developmental Systems 
- (2019) Facial Expression Recognition via Deep Action Units Graph Network Based on Psychological Mechanism [[paper](https://ieeexplore.ieee.org/abstract/document/8721079)]

### :small_orange_diamond: IEEE Transactions on Cybernetics
- (2019) Adaptive Weighting of Handcrafted Feature Losses for Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/document/8786929)]
- (2015) Learning Multiscale Active Facial Patches for Expression Analysis[[paper](https://ieeexplore.ieee.org/document/6912969)]

### :small_orange_diamond: IEEE Transactions on Information Forensics and Security
- (2020) Fine-Grained Facial Expression Recognition in the Wild [[paper](https://ieeexplore.ieee.org/document/9133437)]

### :small_orange_diamond: Computer Vision and Image Understanding
- (2019) Registration-free Face-SSD: Single shot analysis of smiles, facial attributes, and affect in the wild[[paper](https://www.sciencedirect.com/science/article/pii/S1077314219300128)]

### :small_orange_diamond: Pattern Recognition Letters
- (2019) Deep spatial-temporal feature fusion for facial expression recognition
in static images [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0167865517303902)]

## Facial Action Unit Recognition

### :small_orange_diamond: AAAI
- (2021) Uncertain Graph Neural Networks for Facial Action Unit Detection [[paper](https://www.researchgate.net/profile/Tengfei_Song5/publication/346853340_Uncertain_Graph_Neural_Networks_for_Facial_Action_Unit_Detection/links/5fd24e35299bf188d40af784/Uncertain-Graph-Neural-Networks-for-Facial-Action-Unit-Detection.pdf)]
- (2020) Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution [[paper](https://arxiv.org/pdf/2004.09681.pdf)][[Code](https://github.com/EvelynFan/FAU)]
- (2019) Semantic Relationships Guided Representation Learning for Facial Action Unit Recognition [[paper](https://arxiv.org/pdf/1904.09939.pdf)]
- (2019) Dual Semi-Supervised Learning for Facial Action Unit Recognition [[paper](https://www.researchgate.net/publication/335270610_Dual_Semi-Supervised_Learning_for_Facial_Action_Unit_Recognition)]

### :small_orange_diamond: CVPR
- (2019) Joint Representation and Estimator Learning for Facial Action Unit Intensity Estimation [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_Joint_Representation_and_Estimator_Learning_for_Facial_Action_Unit_Intensity_CVPR_2019_paper.pdf)]
- (2019) Self-Supervised Representation Learning From Videos for Facial Action Unit Detection [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Li_Self-Supervised_Representation_Learning_From_Videos_for_Facial_Action_Unit_Detection_CVPR_2019_paper.pdf)]
- (2019) Local Relationship Learning with Person-specific Shape Regularization for
Facial Action Unit Detection [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Niu_Local_Relationship_Learning_With_Person-Specific_Shape_Regularization_for_Facial_Action_CVPR_2019_paper.pdf)]
- (2018) Optimizing Filter Size in Convolutional Neural Networks for Facial Action Unit
Recognition [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Han_Optimizing_Filter_Size_CVPR_2018_paper.pdf)]
- (2018) Weakly-supervised Deep Convolutional Neural Network Learning
for Facial Action Unit Intensity Estimation [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Weakly-Supervised_Deep_Convolutional_CVPR_2018_paper.pdf)]
- (2018) Learning Facial Action Units from Web Images with
Scalable Weakly Supervised Clustering [[paper](http://openaccess.thecvf.com/content_cvpr_2018/CameraReady/0237.pdf)]
- (2018) Classifier Learning with Prior Probabilities
for Facial Action Unit Recognition [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Classifier_Learning_With_CVPR_2018_paper.pdf)]
- (2018) Bilateral Ordinal Relevance Multi-instance Regression
for Facial Action Unit Intensity Estimation [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Bilateral_Ordinal_Relevance_CVPR_2018_paper.pdf)]
- (2018) Weakly Supervised Facial Action Unit Recognition through Adversarial Training [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Peng_Weakly_Supervised_Facial_CVPR_2018_paper.pdf)]
- (2017) Deep Structured Learning for Facial Action Unit Intensity Estimation [[paper](https://arxiv.org/pdf/1704.04481.pdf)]
- (2017) Action Unit Detection with Region Adaptation, Multi-labeling Learning and Optimal Temporal Fusing [[paper](https://arxiv.org/pdf/1704.03067.pdf)]
- (2016) Deep Region and Multi-label Learning for Facial Action Unit Detection [[paper](http://openaccess.thecvf.com/content_cvpr_2016/papers/Zhao_Deep_Region_and_CVPR_2016_paper.pdf)] [[code](https://github.com/zkl20061823/DRML)] [[code2](https://github.com/AlexHex7/DRML_pytorch)]
- (2016) Constrained Joint Cascade Regression Framework for Simultaneous Facial
Action Unit Recognition and Facial Landmark Detection [[paper](http://openaccess.thecvf.com/content_cvpr_2016/papers/Wu_Constrained_Joint_Cascade_CVPR_2016_paper.pdf)]
- (2016) Copula Ordinal Regression
for Joint Estimation of Facial Action Unit Intensity [[paper](https://ibug.doc.ic.ac.uk/media/uploads/documents/copula_ordinal_regression__cvpr2016_final.pdf)] [[code](https://github.com/RWalecki/copula_ordinal_regression)]
- (2015) Latent Trees for Estimating Intensity of Facial Action Units [[paper](https://ibug.doc.ic.ac.uk/media/uploads/documents/kaltwang2015latent.pdf)][[code](https://github.com/kaltwang/latenttrees)]
- (2015) Joint Patch and Multi-label Learning for Facial Action Unit Detection [[paper](http://openaccess.thecvf.com/content_cvpr_2015/papers/Zhao_Joint_Patch_and_2015_CVPR_paper.pdf)]
- (2013) Selective Transfer Machine for Personalized Facial Action Unit Detection [[paper](https://ieeexplore.ieee.org/document/6619295)][:dizzy:]
- (2009) A framework for automated measurement of the intensity of non-posed Facial Action Units [[paper](https://ieeexplore.ieee.org/document/5204259)]

### :small_orange_diamond: ICCV
- (2019) Context-Aware Feature and Label Fusion for Facial Action Unit Intensity Estimation With Partially Labeled Data [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Zhang_Context-Aware_Feature_and_Label_Fusion_for_Facial_Action_Unit_Intensity_ICCV_2019_paper.pdf)]
- (2017) DeepCoder: Semi-parametric Variational Autoencoders
for Automatic Facial Action Coding [[paper](https://ibug.doc.ic.ac.uk/media/uploads/documents/tran_deepcoder_semi-parametric_variational_iccv_2017_paper.pdf)]
- (2017) Deep Facial Action Unit Recognition from Partially Labeled Data [[paper](http://openaccess.thecvf.com/content_ICCV_2017/papers/Wu_Deep_Facial_Action_ICCV_2017_paper.pdf)]
- (2015) Learning to transfer: transferring latent task structures and its application to
person-specific facial action unit detection [[paper](http://openaccess.thecvf.com/content_iccv_2015/papers/Almaev_Learning_to_Transfer_ICCV_2015_paper.pdf)]
- (2015) Multi-conditional Latent Variable Model for Joint Facial Action Unit Detection [[paper](http://openaccess.thecvf.com/content_iccv_2015/papers/Eleftheriadis_Multi-Conditional_Latent_Variable_ICCV_2015_paper.pdf)]
- (2015) Confidence Preserving Machine for Facial Action Unit Detection [[paper](http://openaccess.thecvf.com/content_iccv_2015/papers/Zeng_Confidence_Preserving_Machine_ICCV_2015_paper.pdf)]

### :small_orange_diamond: ECCV
- (2018) Deep Structure Inference Network for Facial
Action Unit Recognition [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Ciprian_Corneanu_Deep_Structure_Inference_ECCV_2018_paper.pdf)]
- (2018) Deep Adaptive Attention for Joint Facial Action
Unit Detection and Face Alignment[[paper](https://arxiv.org/pdf/1803.05588.pdf)] 

### :small_orange_diamond: NIPS
- (2020) Knowledge Augmented Deep Neural Networks for
Joint Facial Expression and Action Unit Recognition [[paper](https://papers.nips.cc/paper/2020/file/a51fb975227d6640e4fe47854476d133-Paper.pdf)]
- (2019) Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition [[paper](https://nxsedson.github.io/paper/NeurIPS2019.pdf)]
- (2016) Incremental Boosting Convolutional Neural Network
for Facial Action Unit Recognition [[paper](https://arxiv.org/pdf/1707.05395.pdf)] 

### :small_orange_diamond: ACM MM
- (2020) Adaptive Multimodal Fusion for Facial Action Units Recognition [[paper](https://dl.acm.org/doi/pdf/10.1145/3394171.3413538)]
- (2020) Region of Interest Based Graph Convolution: A Heatmap
Regression Approach for Action Unit Detection [[paper](https://dl.acm.org/doi/pdf/10.1145/3394171.3413674)]
- (2020) Unsupervised Learning Facial Parameter Regressor for Action
Unit Intensity Estimation via Differentiable Renderer [[paper](https://arxiv.org/pdf/2008.08862.pdf)]
- (2018) Personalized Multiple Facial Action Unit Recognition through
Generative Adversarial Recognition Network [[paper](https://dl.acm.org/citation.cfm?id=3240613)]

### :small_orange_diamond: BMVC
- (2020) Self-Supervised Learning for Facial Action Unit Recognition through Temporal Consistency [[paper](https://www.bmvc2020-conference.com/assets/papers/0861.pdf)][[code](https://github.com/intelligent-human-perception-laboratory/temporal-consistency)]
- (2019) Unmasking the Devil in the Details:What Works for Deep Facial Action Coding? [[paper](https://bmvc2019.org/wp-content/uploads/papers/0403-paper.pdf)]
- (2019) Large Margin Loss for Learning Facial
Movements from Pseudo-Emotions [[paper](https://bmvc2019.org/wp-content/uploads/papers/0498-paper.pdf)]
- (2019) Attention-based Facial Behavior Analytics in
Social Communication [[paper](https://bmvc2019.org/wp-content/uploads/papers/0491-paper.pdf)]
- (2019) Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace [[paper](https://bmvc2019.org/wp-content/uploads/papers/0399-paper.pdf)]
- (2019) PAttNet: Patch-attentive deep network for action unit detection [[paper](https://www.jeffcohn.net/wp-content/uploads/2019/07/BMVC2019_PAttNet.pdf.pdf)]
- (2018) Identity-based Adversarial Training of Deep
CNNs for Facial Action Unit Recognition [[paper](http://bmvc2018.org/contents/papers/0741.pdf)]
- (2018) Joint Action Unit localisation and intensity
estimation through heatmap regression [[paper](https://arxiv.org/pdf/1805.03487.pdf)] [[code](https://github.com/ESanchezLozano/Action-Units-Heatmaps)] [:dizzy::dizzy::dizzy::dizzy:]

### :small_orange_diamond: FG
- (2019) Expression Empowered ResiDen Network for Facial Action Unit Detection [[paper](https://ieeexplore-ieee-org/document/8756580)]
- (2019) IdenNet: Identity-Aware Facial Action Unit Detection [[paper](https://ieeexplore-ieee-org/document/8756631)]
- (2019) Multimodal Deep Feature Aggregation for Facial Action Unit Recognition using Visible Images and Physiological Signals [[paper](https://ieeexplore-ieee-org/document/8756629)]
- (2019) Facial Action Unit Analysis through 3D Point Cloud Neural Networks [[paper](https://ieeexplore-ieee-org/document/8756610)]
- (2018) Edge Convolutional Network for Facial Action Intensity Estimation [[paper](https://ieeexplore.ieee.org/document/8373827/)]
- (2017) Support Vector Regression of Sparse Dictionary-Based Features for View-Independent Action Unit Intensity Estimation [[paper](https://ieeexplore.ieee.org/document/7961832)]
- (2017) Pose-independent Facial Action Unit Intensity Regression Based on
Multi-task Deep Transfer Learning [[paper](https://ieeexplore.ieee.org/document/7961835)]
- (2017) AUMPNet: Simultaneous Action Units Detection and Intensity Estimation on Multipose Facial Images Using a Single Convolutional Neural Network [[paper](https://www.researchgate.net/publication/315952013_AUMPNet_Simultaneous_Action_Units_Detection_and_Intensity_Estimation_on_Multipose_Facial_Images_Using_a_Single_Convolutional_Neural_Network)]
- (2017) EAC-Net: A Region-based Deep Enhancing and Cropping Approach for
Facial Action Unit Detection [[paper](https://arxiv.org/pdf/1702.02925.pdf)]
- (2015) Deep Learning based FACS Action Unit Occurrence and Intensity
Estimation [[paper](https://ieeexplore.ieee.org/document/7284873)]
- (2015) How much training data for facial action unit detection? [[paper](https://ieeexplore.ieee.org/document/7163106)]
- (2015) Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine [[paper](https://ieeexplore.ieee.org/document/7284870)]
- (2015) A Unified Probabilistic Framework For Measuring The Intensity of
Spontaneous Facial Action Units [[paper](https://ieeexplore.ieee.org/document/6553757)]

### :small_orange_diamond: ICIP
- (2019) Multi-Task Learning of Emotion Recognition and Facial Action Unit Detection with Adaptively Weights Sharing Network [[paper](https://ieeexplore.ieee.org/abstract/document/8802914)]
- (2014) Facial action unit intensity estimation using rotation invariant features and regression analysis [[paper](https://ieeexplore.ieee.org/abstract/document/7025276)]

### :small_orange_diamond: IEEE Transactions on Image Processing (TIP)
- (2018) Facial Action Unit Recognition and Intensity Estimation Enhanced Through Label Dependencies [[paper](https://www.researchgate.net/publication/328548884_Facial_Action_Unit_Recognition_and_Intensity_Estimation_Enhanced_Through_Label_Dependencies)]
- (2017) Learning Bases of Activity for Facial Expression Recognition [[paper](https://ieeexplore.ieee.org/document/7839217)]
- (2016) Joint Patch and Multi-label Learning for Facial
Action Unit and Holistic Expression Recognition [[paper](http://www.humansensing.cs.cmu.edu/sites/default/files/07471506.pdf)]

### :small_orange_diamond: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- (2020) Learning Representations for Facial Actions from Unlabeled Videos [[paper](https://www.computer.org/csdl/journal/tp/5555/01/09145674/1lE04DpfpyE)]
- (2015) Discriminant Functional Learning of Color
Features for the Recognition of Facial Action
Units and their Intensities [[paper](https://ieeexplore.ieee.org/document/8454901)]
- (2015) Context-Sensitive Dynamic Ordinal Regression
for Intensity Estimation of Facial Action Units [[paper](https://spiral.imperial.ac.uk/bitstream/10044/1/23471/2/tpamicscorffinal_rudovic.pdf)]

### :small_orange_diamond: IEEE Transactions on Affective Computing (TAC)
- (2020) RFAU: A Database for Facial Action Unit Analysis in Real Classrooms [[paper](https://ieeexplore.ieee.org/document/9130811)]
- (2019) Listen to Your Face: Inferring Facial Action
Units from Audio Channel [[paper](https://ieeexplore.ieee.org/document/8025777)]
- (2019) Deep Facial Action Unit Recognition and Intensity Estimation from Partially Labelled Data [[paper](https://ieeexplore.ieee.org/abstract/document/8705351)]
- (2019) Capturing Feature and Label Relations Simultaneously for Multiple Facial Action Unit Recognition [[paper](https://ieeexplore.ieee.org/document/8006290)]
- (2019) An Adaptive Bayesian Source Separation Method for Intensity Estimation of Facial AUs [[paper](https://ieeexplore.ieee.org/document/7933209)]
- (2017) Copula Ordinal Regression Framework
for Joint Estimation of Facial Action Unit Intensity[[paper](https://ibug.doc.ic.ac.uk/media/uploads/documents/07983431.pdf)]

### :small_orange_diamond: IEEE Transactions on Cybernetics
- (2020) Dual Learning for Facial Action Unit Detection
Under Nonfull Annotation [[paper](https://ieeexplore.ieee.org/abstract/document/9139271)]
- (2017) Improving Speech Related Facial Action Unit
Recognition by Audiovisual Information Fusion [[paper](https://arxiv.org/pdf/1706.10197.pdf)]
- (2016) Intensity Estimation of Spontaneous Facial Action Units Based on Their Sparsity Properties [[paper](https://ieeexplore.ieee.org/document/7081360)]

### :small_orange_diamond: International Journal of Computer Vision (IJCV)
- (2019) A Spatiotemporal Convolutional Neural Network for Automatic Pain
Intensity Estimation from Facial Dynamics [[paper](https://link.springer.com/content/pdf/10.1007/s11263-019-01191-3.pdf)]

### :small_orange_diamond: Pattern Recognition (PR)
- (2019) Domain Adaptive Representation Learning for Facial Action Unit Recognition [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320319304285)]
- (2017) Feature and label relation modeling for multiple-facial action unit
classification and intensity estimation [[paper](https://www.ecse.rpi.edu/~cvrl/Publication/pdf/Wang2017a.pdf)]
- (2017) Expression-assisted facial action unit
recognition under incomplete Au annotation [[paper](https://www.ecse.rpi.edu/~cvrl/Publication/pdf/Wang2017.pdf)]
- (2016) Task-dependent multi-task multiple kernel learning for facial action unit detection [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320315003143)]

### :small_orange_diamond: Image and Vision Computing
- (2016) Real-time facial action unit intensity prediction with regularized
metric learning [[paper](https://www.sciencedirect.com/science/article/pii/S0262885616300300)]
- (2012) Regression-based intensity estimation of facial action units [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0262885611001326)]

### :small_orange_diamond: Neurocomputing
- (2020) Action Unit Analysis Enhanced Facial Expression Recognition by
Deep Neural Network Evolution [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0925231220303891)]
- (2019) AU R-CNN：Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection [[paper](https://www.sciencedirect.com/science/article/abs/pii/S0925231219305338)]

### :small_orange_diamond: Journal of Visual Communication and Image Representation 
- (2017) A joint dictionary learning and regression model for intensity estimation of facial AUs [[paper](https://www.sciencedirect.com/science/article/pii/S1047320317301025)]

## Affective Level Estimation

### :small_orange_diamond: Valence-Arousal Level Estimation
- (CVPR 2020) Factorized Higher-Order CNNs
with an Application to Spatio-Temporal Emotion Estimation [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Kossaifi_Factorized_Higher-Order_CNNs_With_an_Application_to_Spatio-Temporal_Emotion_Estimation_CVPR_2020_paper.pdf)]
- (AAAI 2020) MIMAMO Net: Integrating Micro- and Macro-motion for Video Emotion
Recognition [[paper](https://arxiv.org/pdf/1911.09784.pdf)]
- (BMVC 2019) An Unsupervised Subspace Ranking Method
for Continuous Emotions in Face Images [[paper](https://bmvc2019.org/wp-content/uploads/papers/0831-paper.pdf)]
- (CVPRW 2017) Estimation of Affective Level in the Wild
With Multiple Memory Networks [[paper](http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/papers/Li_Estimation_of_Affective_CVPR_2017_paper.pdf)][:dizzy::dizzy:]
- (CVPRW 2016) Automatic Recognition of Emotions and Membership in Group Videos [[paper](http://openaccess.thecvf.com/content_cvpr_2016_workshops/w28/papers/Mou_Automatic_Recognition_of_CVPR_2016_paper.pdf)][:dizzy:]
- (IEEE trans on Affective Computing 2011) Continuous Prediction of Spontaneous Affect from Multiple Cues and Modalities in Valence-Arousal Space [[paper](https://ieeexplore.ieee.org/document/5740839)]

### :small_orange_diamond: Smile Intensity Estimation
- (ICMI 2016) Happiness level prediction with sequential inputs via multiple regressions [[paper](https://www.researchgate.net/publication/309614650_Happiness_level_prediction_with_sequential_inputs_via_multiple_regressions)]
- (Pattern Recognition Letters 2014) Estimating smile intensity: A better way [[paper](https://www.researchgate.net/publication/266672947_Estimating_smile_intensity_A_better_way)] [:dizzy::dizzy::dizzy::dizzy:]
- (Multimedia Tools and Applications 2018) Smile intensity recognition in real time videos: fuzzy system approach[[paper](https://link.springer.com/article/10.1007/s11042-018-6890-8)]
- (ACM Transactions on Intelligent Systems and Technology 2018) The Effect of Pets on Happiness: A Large-Scale Multi-Factor
Analysis Using Social Multimedia [[paper](https://arxiv.org/pdf/1804.03507.pdf)]
- (ICMI 2016) Group Happiness Assessment Using Geometric Features
and Dataset Balancing [[paper](http://vintage.winklerbros.net/Publications/emotiw2016.pdf)]
- (ICMSS 2017) Happy Index: Analysis Based on Automatic Recognition of
Emotion Flow [[paper](https://www.researchgate.net/publication/315605704_Happy_Index_Analysis_Based_on_Automatic_Recognition_of_Emotion_Flow)]
- (ICCVW 2017) SmileNet: Registration-Free Smiling Face Detection In The Wild [[paper](http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w23/Jang_SmileNet_Registration-Free_Smiling_ICCV_2017_paper.pdf)][[project](https://sites.google.com/view/sensingfeeling/)]
- (ACII 2017) Smiling from Adolescence to Old Age: A Large Observational Study [[paper](https://ieeexplore.ieee.org/document/8273585)]
- (ACCVW 2010) Appearance-based smile intensity estimation by cascaded support vector machines [[paper](https://dl.acm.org/doi/10.5555/2040690.2040720)]

### :small_orange_diamond: Painful Expression Intensity Estimation
- (ICPR 2018) Deep Spatiotemporal Representation of the Face
for Automatic Pain Intensity Estimation [[paper](https://arxiv.org/pdf/1806.06793.pdf)]
- (IEEE Transactions on Affective Computing 2019) Multi-modal Pain Intensity Recognition based on the SenseEmotion Database [[paper](https://ieeexplore.ieee.org/document/8607037)]
- (CVPR 2017) Personalized Automatic Estimation of Self-reported Pain Intensity
from Facial Expressions [[paper](https://ieeexplore.ieee.org/document/8015020)][:dizzy::dizzy:]
- (IEEE Transactions on Affective Computing 2017) Learning Pain from Action Unit Combinations: A Weakly Supervised Approach via Multiple Instance Learning [[paper](https://www.researchgate.net/publication/321570917_Learning_Pain_from_Action_Unit_Combinations_A_Weakly_Supervised_Approach_via_Multiple_Instance_Learning)]
- (IEEE trans on Affective Computing 2017) Automatic Pain Assessment with Facial
Activity Descriptors [[paper](https://ieeexplore.ieee.org/document/7423704)]
- (CVPR 2017) Personalized Automatic Estimation of Self-reported Pain Intensity
from Facial Expressions [[paper](https://arxiv.org/pdf/1706.07154.pdf)]
- (ICIP 2017) Regularizing Face Verification Nets for Pain Intensity Regression [[paper](https://arxiv.org/pdf/1702.06925.pdf)][[code](https://github.com/happynear/PainRegression)]
- (CVPRW 2017) Personalized Automatic Estimation of Self-reported Pain Intensity
from Facial Expressions [[paper](http://openaccess.thecvf.com/content_cvpr_2017_workshops/w41/papers/Picard_Personalized_Automatic_Estimation_CVPR_2017_paper.pdf)][:dizzy::dizzy:]
- (ICMI 2017) Cumulative Attributes for Pain Intensity Estimation [[paper](https://dl.acm.org/doi/10.1145/3136755.3136789)]
- (CVPRW 2017) Recurrent Convolutional Neural Network Regression for Continuous Pain Intensity Estimation in Video [[paper](https://arxiv.org/pdf/1605.00894.pdf)]
- (CVPRW 2016)Recurrent Convolutional Neural Network Regression for Continuous Pain
Intensity Estimation in Video[[paper](https://ieeexplore.ieee.org/document/7789681)][:dizzy::dizzy::dizzy:]
- (CVPRW 2015)Pain Recognition using Spatiotemporal Oriented Energy of Facial Muscles[[paper](https://ieeexplore.ieee.org/document/7301340)]
- (FG 2015)Weakly Supervised Pain Localization using Multiple Instance Learning [[paper](https://ieeexplore.ieee.org/document/6553762)]
- (ICPR 2014) Pain Intensity Evaluation Through Facial Action
Units [[paper](https://ieeexplore.ieee.org/document/6977516)]