AFEW-VA database for valence and arousal estimation in-the-wild
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Maja Pantic | Jean Kossaifi | Georgios Tzimiropoulos | Sinisa Todorovic | M. Pantic | S. Todorovic | Jean Kossaifi | Georgios Tzimiropoulos
[1] Catherine Pelachaud,et al. A multimodal fuzzy inference system using a continuous facial expression representation for emotion detection , 2012, ICMI '12.
[2] William M. Campbell,et al. Multi-Modal Audio, Video and Physiological Sensor Learning for Continuous Emotion Prediction , 2016, AVEC@ACM Multimedia.
[3] Zhihong Zeng,et al. A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[4] Shaogang Gong,et al. Facial expression recognition based on Local Binary Patterns: A comprehensive study , 2009, Image Vis. Comput..
[5] Stefanos Zafeiriou,et al. Correlated-spaces regression for learning continuous emotion dimensions , 2013, MM '13.
[6] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[7] Ya Li,et al. Long Short Term Memory Recurrent Neural Network based Multimodal Dimensional Emotion Recognition , 2015, AVEC@ACM Multimedia.
[8] Ya Li,et al. Multi-scale Temporal Modeling for Dimensional Emotion Recognition in Video , 2014, AVEC '14.
[9] Sven Behnke,et al. PyStruct: learning structured prediction in python , 2014, J. Mach. Learn. Res..
[10] John Cosmas,et al. Time-Delay Neural Network for Continuous Emotional Dimension Prediction From Facial Expression Sequences , 2016, IEEE Transactions on Cybernetics.
[11] Björn W. Schuller,et al. Categorical and dimensional affect analysis in continuous input: Current trends and future directions , 2013, Image Vis. Comput..
[12] Vladimir Pavlovic,et al. Copula Ordinal Regression for Joint Estimation of Facial Action Unit Intensity , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Maja Pantic,et al. The first facial expression recognition and analysis challenge , 2011, Face and Gesture 2011.
[14] Dongmei Jiang,et al. Multimodal Affective Dimension Prediction Using Deep Bidirectional Long Short-Term Memory Recurrent Neural Networks , 2015, AVEC@ACM Multimedia.
[15] Hatice Gunes,et al. Continuous Prediction of Spontaneous Affect from Multiple Cues and Modalities in Valence-Arousal Space , 2011, IEEE Transactions on Affective Computing.
[16] Mohammad Soleymani,et al. A Multimodal Database for Affect Recognition and Implicit Tagging , 2012, IEEE Transactions on Affective Computing.
[17] Albert Ali Salah,et al. Ensemble CCA for Continuous Emotion Prediction , 2014, AVEC '14.
[18] K. Kroschel,et al. Evaluation of natural emotions using self assessment manikins , 2005, IEEE Workshop on Automatic Speech Recognition and Understanding, 2005..
[19] Peter Robinson,et al. Dimensional affect recognition using Continuous Conditional Random Fields , 2013, 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).
[20] Vladimir Pavlovic,et al. Context-Sensitive Dynamic Ordinal Regression for Intensity Estimation of Facial Action Units , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[21] L. Rothkrantz,et al. Toward an affect-sensitive multimodal human-computer interaction , 2003, Proc. IEEE.
[22] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[23] Maja Pantic,et al. Fast and exact bi-directional fitting of active appearance models , 2015, 2015 IEEE International Conference on Image Processing (ICIP).
[24] Björn W. Schuller,et al. AVEC 2013: the continuous audio/visual emotion and depression recognition challenge , 2013, AVEC@ACM Multimedia.
[25] Xiaogang Wang,et al. Hybrid Deep Learning for Face Verification , 2013, 2013 IEEE International Conference on Computer Vision.
[26] Matti Pietikäinen,et al. Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[27] Andrea Cavallaro,et al. Automatic Analysis of Facial Affect: A Survey of Registration, Representation, and Recognition , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[28] Tamás D. Gedeon,et al. Collecting Large, Richly Annotated Facial-Expression Databases from Movies , 2012, IEEE MultiMedia.
[29] Vladimir Pavlovic,et al. Dynamic Probabilistic CCA for Analysis of Affective Behaviour , 2012, ECCV.
[30] Ting Dang,et al. An Investigation of Annotation Delay Compensation and Output-Associative Fusion for Multimodal Continuous Emotion Prediction , 2015, AVEC@ACM Multimedia.
[31] Enrique Argones-Rúa,et al. Audiovisual three-level fusion for continuous estimation of Russell's emotion circumplex , 2013, AVEC@ACM Multimedia.
[32] Markus Kächele,et al. Inferring Depression and Affect from Application Dependent Meta Knowledge , 2014, AVEC '14.
[33] Patrick Thiam,et al. Ensemble Methods for Continuous Affect Recognition: Multi-modality, Temporality, and Challenges , 2015, AVEC@ACM Multimedia.
[34] Margaret McRorie,et al. The Belfast Induced Natural Emotion Database , 2012, IEEE Transactions on Affective Computing.
[35] Maja Pantic,et al. Fast Newton active appearance models , 2014, 2014 IEEE International Conference on Image Processing (ICIP).
[36] Maja Pantic,et al. Doubly Sparse Relevance Vector Machine for Continuous Facial Behavior Estimation , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[37] Shrikanth S. Narayanan,et al. The Vera am Mittag German audio-visual emotional speech database , 2008, 2008 IEEE International Conference on Multimedia and Expo.
[38] Hatice Gunes,et al. Output-associative RVM regression for dimensional and continuous emotion prediction , 2011, Face and Gesture 2011.
[39] Maja Pantic,et al. Meta-Analysis of the First Facial Expression Recognition Challenge , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[40] Stefanos Zafeiriou,et al. Robust Correlated and Individual Component Analysis , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[41] Vladimir Pavlovic,et al. Multi-output Laplacian dynamic ordinal regression for facial expression recognition and intensity estimation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[42] Fabien Ringeval,et al. Introducing the RECOLA multimodal corpus of remote collaborative and affective interactions , 2013, 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).
[43] Mohamed Chetouani,et al. Robust continuous prediction of human emotions using multiscale dynamic cues , 2012, ICMI '12.
[44] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[45] Björn W. Schuller,et al. AVEC 2014: 3D Dimensional Affect and Depression Recognition Challenge , 2014, AVEC '14.
[46] Qin Jin,et al. Multi-modal Dimensional Emotion Recognition using Recurrent Neural Networks , 2015, AVEC@ACM Multimedia.
[47] Thierry Pun,et al. DEAP: A Database for Emotion Analysis ;Using Physiological Signals , 2012, IEEE Transactions on Affective Computing.
[48] Maja Pantic,et al. Machine analysis of facial behaviour: naturalistic and dynamic behaviour , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.
[49] Matthijs C. Dorst. Distinctive Image Features from Scale-Invariant Keypoints , 2011 .
[50] B. Heisele. Face Detection , 2001 .
[51] Patrick Cardinal,et al. ETS System for AV+EC 2015 Challenge , 2015, AVEC@ACM Multimedia.
[52] Gregory K. Wallace,et al. The JPEG still picture compression standard , 1992 .
[53] Maja Pantic,et al. Latent trees for estimating intensity of Facial Action Units , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[54] Maja Pantic,et al. Continuous Pain Intensity Estimation from Facial Expressions , 2012, ISVC.
[55] Yang Li,et al. 3D model-based continuous emotion recognition , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[56] Tamás D. Gedeon,et al. Emotion Recognition In The Wild Challenge 2014: Baseline, Data and Protocol , 2014, ICMI.
[57] Maja Pantic,et al. Fast and Exact Newton and Bidirectional Fitting of Active Appearance Models , 2017, IEEE Transactions on Image Processing.
[58] Björn W. Schuller,et al. AVEC 2011-The First International Audio/Visual Emotion Challenge , 2011, ACII.
[59] Daniel McDuff,et al. Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild" , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.
[60] J. Fleiss,et al. Intraclass correlations: uses in assessing rater reliability. , 1979, Psychological bulletin.
[61] Lionel Prevost,et al. Facial Action Recognition Combining Heterogeneous Features via Multikernel Learning , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[62] Heng Wang,et al. Depression recognition based on dynamic facial and vocal expression features using partial least square regression , 2013, AVEC@ACM Multimedia.
[63] Björn W. Schuller,et al. Abandoning emotion classes - towards continuous emotion recognition with modelling of long-range dependencies , 2008, INTERSPEECH.
[64] Yves Grandvalet,et al. Y.: SimpleMKL , 2008 .
[65] Bo Sun,et al. Exploring Multimodal Visual Features for Continuous Affect Recognition , 2016, AVEC@ACM Multimedia.
[66] Fabien Ringeval,et al. AVEC 2016: Depression, Mood, and Emotion Recognition Workshop and Challenge , 2016, AVEC@ACM Multimedia.
[67] Björn W. Schuller,et al. AVEC 2012: the continuous audio/visual emotion challenge , 2012, ICMI '12.
[68] N. Ahmed,et al. Discrete Cosine Transform , 2019, IEEE Transactions on Computers.
[69] Maja Pantic,et al. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING , 2022 .
[70] Kostas Karpouzis,et al. The HUMAINE Database: Addressing the Collection and Annotation of Naturalistic and Induced Emotional Data , 2007, ACII.
[71] Tanaya Guha,et al. Multimodal Prediction of Affective Dimensions and Depression in Human-Computer Interactions , 2014, AVEC '14.
[72] Mohammad H. Mahoor,et al. DISFA: A Spontaneous Facial Action Intensity Database , 2013, IEEE Transactions on Affective Computing.
[73] Alessandro Rozza,et al. Multimodal Affective Analysis combining Regularized Linear Regression and Boosted Regression Trees , 2015, AVEC@ACM Multimedia.
[74] Roddy Cowie,et al. FEELTRACE: an instrument for recording perceived emotion in real time , 2000 .
[75] Rahul Gupta,et al. Online Affect Tracking with Multimodal Kalman Filters , 2016, AVEC@ACM Multimedia.
[76] Maja Pantic,et al. The MAHNOB Laughter database , 2013, Image Vis. Comput..
[77] Deva Ramanan,et al. Face detection, pose estimation, and landmark localization in the wild , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[78] Anton Nijholt,et al. The MAHNOB Mimicry Database: A database of naturalistic human interactions , 2015, Pattern Recognit. Lett..
[79] Patrick Thiam,et al. Continuous Multimodal Human Affect Estimation using Echo State Networks , 2016, AVEC@ACM Multimedia.
[80] Rich Caruana,et al. An empirical evaluation of supervised learning in high dimensions , 2008, ICML '08.
[81] Pavel Matejka,et al. Multimodal Emotion Recognition for AVEC 2016 Challenge , 2016, AVEC@ACM Multimedia.
[82] Shiguang Shan,et al. Learning Expressionlets on Spatio-temporal Manifold for Dynamic Facial Expression Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[83] Jean-Philippe Thiran,et al. Prediction of asynchronous dimensional emotion ratings from audiovisual and physiological data , 2015, Pattern Recognit. Lett..
[84] Etienne B. Roesch,et al. A Blueprint for Affective Computing: A Sourcebook and Manual , 2010 .
[85] Björn W. Schuller,et al. A demonstration of audiovisual sensitive artificial listeners , 2009, 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops.