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Emotion Recognition In The Wild Challenge 2014

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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AVEC 2011–The First International Audio/Visual Emotion Challenge

inferredcites →https://doi.org/10.1007/978-3-642-37444-9_48openalex-snapshot

Finding Happiest Moments in a Social Context

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Pictorial Structures for Object Recognition

inferredcites →https://doi.org/10.1109/acii.2009.5349350openalex-snapshot

OpenEAR — Introducing the munich open-source emotion and affect recognition toolkit

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Comprehensive database for facial expression analysis

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Multi-PIE

inferredcites →https://doi.org/10.1109/cvpr.2012.6248014openalex-snapshot

Face detection, pose estimation, and landmark localization in the wild

inferredcites →https://doi.org/10.1109/cvpr.2013.75openalex-snapshot

Supervised Descent Method and Its Applications to Face Alignment

inferredcites →https://doi.org/10.1109/fg.2013.6553762openalex-snapshot

Weakly supervised pain localization using multiple instance learning

inferredcites →https://doi.org/10.1109/iccvw.2011.6130508openalex-snapshot

Static facial expression analysis in tough conditions: Data, evaluation protocol and benchmark

inferredcites →https://doi.org/10.1109/icme.2006.262433openalex-snapshot

Efficient Recognition of Authentic Dynamic Facial Expressions on the Feedtum Database

inferredcites →https://doi.org/10.1109/mmul.2012.26openalex-snapshot

Collecting Large, Richly Annotated Facial-Expression Databases from Movies

inferredcites →https://doi.org/10.1109/tpami.2007.1110openalex-snapshot

Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions

inferredcites →https://doi.org/10.1109/tpami.2009.42openalex-snapshot

Toward Practical Smile Detection

inferredcites →https://doi.org/10.1109/wacv.2014.6835729openalex-snapshot

A discriminative parts based model approach for fiducial points free and shape constrained head pose normalisation in the wild

inferredcites →https://doi.org/10.1109/wacv.2014.6835991openalex-snapshot

A discriminative parts based model approach for fiducial points free and shape constrained head pose normalisation in the wild

inferredcites →https://doi.org/10.1145/1873951.1874246openalex-snapshot

Opensmile

inferredcites →https://doi.org/10.1145/2522848.2531738openalex-snapshot

Partial least squares regression on grassmannian manifold for emotion recognition

inferredcites →https://doi.org/10.1145/2522848.2531739openalex-snapshot

Emotion recognition in the wild challenge 2013

inferredcites →https://doi.org/10.1145/2522848.2531741openalex-snapshot

Multiple kernel learning for emotion recognition in the wild

inferredcites →https://doi.org/10.1145/2522848.2531745openalex-snapshot

Combining modality specific deep neural networks for emotion recognition in video

inferredcites →https://doi.org/10.21437/interspeech.2010-739openalex-snapshot

The INTERSPEECH 2010 paralinguistic challenge

inferredcites →https://doi.org/10.4304/jmm.1.6.22-35openalex-snapshot

Automatic Recognition of Facial Actions in Spontaneous Expressions

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Multimodal Fusion of Spatial-Temporal Features for Emotion Recognition in the Wild

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Deep Affect Prediction in-the-Wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond

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Facial Emotion Recognition in-the-Wild Using Deep Neural Networks: A Comprehensive Review

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Dynamic Facial Expression Recognition With Atlas Construction and Sparse Representation

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Sparse Kernel Reduced-Rank Regression for Bimodal Emotion Recognition From Facial Expression and Speech

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Sparse Representation Classifier Guided Grassmann Reconstruction Metric Learning With Applications to Image Set Analysis

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Uncertain Facial Expression Recognition via Multi-Task Assisted Correction

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SymNet: A Simple Symmetric Positive Definite Manifold Deep Learning Method for Image Set Classification

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Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications

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A Functional Regression Approach to Facial Landmark Tracking

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Neural Networks for Emotion Recognition in the Wild

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Emotion Recognition in the Wild

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Combining Modality-Specific Extreme Learning Machines for Emotion Recognition in the Wild

inferred← citeshttps://doi.org/10.1145/2663204.2666274openalex-snapshot

Combining Multiple Kernel Methods on Riemannian Manifold for Emotion Recognition in the Wild

inferred← citeshttps://doi.org/10.1145/2663204.2666276openalex-snapshot

Enhanced Autocorrelation in Real World Emotion Recognition

inferred← citeshttps://doi.org/10.1145/2663204.2666277openalex-snapshot

Emotion Recognition in the Wild with Feature Fusion and Multiple Kernel Learning

inferred← citeshttps://doi.org/10.1145/2663204.2666278openalex-snapshot

Improved Spatiotemporal Local Monogenic Binary Pattern for Emotion Recognition in The Wild

inferred← citeshttps://doi.org/10.1145/2663204.2666279openalex-snapshot

Emotion Recognition in Real-world Conditions with Acoustic and Visual Features

inferred← citeshttps://doi.org/10.1145/2663204.2666284openalex-snapshot

Speaker- and Corpus-Independent Methods for Affect Classification in Computational Paralinguistics

inferred← citeshttps://doi.org/10.1145/2668024.2668025openalex-snapshot

Continuous Mapping of Personality Traits

inferred← citeshttps://doi.org/10.1145/2733373.2806408openalex-snapshot

AVEC 2015

inferred← citeshttps://doi.org/10.1145/2745197.2755512openalex-snapshot

SensiTV

inferred← citeshttps://doi.org/10.1145/2808196.2811636openalex-snapshot

Multimodal Affective Analysis combining Regularized Linear Regression and Boosted Regression Trees

inferred← citeshttps://doi.org/10.1145/2813524.2813526openalex-snapshot

Affect Recognition in a Realistic Movie Dataset Using a Hierarchical Approach

inferred← citeshttps://doi.org/10.1145/2818346.2823317openalex-snapshot

Micro-opinion Sentiment Intensity Analysis and Summarization in Online Videos

inferred← citeshttps://doi.org/10.1145/2818346.2829994openalex-snapshot

Video and Image based Emotion Recognition Challenges in the Wild

inferred← citeshttps://doi.org/10.1145/2818346.2830582openalex-snapshot

Multiple Models Fusion for Emotion Recognition in the Wild

inferred← citeshttps://doi.org/10.1145/2818346.2830583openalex-snapshot

A Deep Feature based Multi-kernel Learning Approach for Video Emotion Recognition

inferred← citeshttps://doi.org/10.1145/2818346.2830584openalex-snapshot

Transductive Transfer LDA with Riesz-based Volume LBP for Emotion Recognition in The Wild

inferred← citeshttps://doi.org/10.1145/2818346.2830585openalex-snapshot

Capturing AU-Aware Facial Features and Their Latent Relations for Emotion Recognition in the Wild

inferred← citeshttps://doi.org/10.1145/2818346.2830588openalex-snapshot

Contrasting and Combining Least Squares Based Learners for Emotion Recognition in the Wild

inferred← citeshttps://doi.org/10.1145/2818346.2830595openalex-snapshot

Image based Static Facial Expression Recognition with Multiple Deep Network Learning

inferred← citeshttps://doi.org/10.1145/2818346.2830596openalex-snapshot

Recurrent Neural Networks for Emotion Recognition in Video

inferred← citeshttps://doi.org/10.1145/2988257.2988270openalex-snapshot

Exploring Multimodal Visual Features for Continuous Affect Recognition

inferred← citeshttps://doi.org/10.1145/2993148.2997631openalex-snapshot

Multi-view common space learning for emotion recognition in the wild

inferred← citeshttps://doi.org/10.1145/2993148.2997634openalex-snapshot

Automatic emotion recognition in the wild using an ensemble of static and dynamic representations

inferred← citeshttps://doi.org/10.1145/2993148.2997637openalex-snapshot

Audio and face video emotion recognition in the wild using deep neural networks and small datasets

inferred← citeshttps://doi.org/10.1145/2993148.2997638openalex-snapshot

EmotiW 2016: video and group-level emotion recognition challenges

inferred← citeshttps://doi.org/10.1145/2993148.2997639openalex-snapshot

HoloNet: towards robust emotion recognition in the wild

inferred← citeshttps://doi.org/10.1145/3129340openalex-snapshot

Speech emotion recognition

inferred← citeshttps://doi.org/10.1145/3130859.3131433openalex-snapshot

Integrating Affective Responses and Gamification into Early Reading Acquisition Software Applications

inferred← citeshttps://doi.org/10.1145/3131287openalex-snapshot

Emotion Recognition Using Multiple Kernel Learning toward E-learning Applications

inferred← citeshttps://doi.org/10.1145/3136755.3143009openalex-snapshot

Learning supervised scoring ensemble for emotion recognition in the wild

inferred← citeshttps://doi.org/10.1145/3152771.3156179openalex-snapshot

Discriminating real and posed smiles

inferred← citeshttps://doi.org/10.1145/3184066.3184086openalex-snapshot

Audio-based emotion recognition using GMM supervector an SVM linear kernel

inferred← citeshttps://doi.org/10.1145/3372938.3372966openalex-snapshot

Driver State Monitoring System

inferred← citeshttps://doi.org/10.1145/3411763.3451813openalex-snapshot

Can Binaural Beats Increase Your Focus? Exploring the Effects of Music in Participants’ Conscious and Brain Activity Responses

inferred← citeshttps://doi.org/10.1145/3426020.3426122openalex-snapshot

Multiple Models Using Temporal Feature Learning for Emotion Recognition

inferred← citeshttps://doi.org/10.1145/3577190.3616545openalex-snapshot

EmotiW 2023: Emotion Recognition in the Wild Challenge

inferred← citeshttps://doi.org/10.1145/3581783.3612836openalex-snapshot

MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning

inferred← citeshttps://doi.org/10.1145/3617023.3617032openalex-snapshot

Automatic Emotion Detection in the Learning of Algorithms

inferred← citeshttps://doi.org/10.1145/3708498openalex-snapshot

A Survey of Geometric Optimization for Deep Learning: From Euclidean Space to Riemannian Manifold

inferred← citeshttps://doi.org/10.1155/2016/4789803openalex-snapshot

User Adaptive and Context-Aware Smart Home Using Pervasive and Semantic Technologies

inferred← citeshttps://doi.org/10.1155/hbe2/7777949openalex-snapshot

The Role of Time in Facial Dynamics and Challenges in Automatic Emotion Recognition (2019–2024)

inferred← citeshttps://doi.org/10.11591/ijeecs.v25.i3.pp1489-1500openalex-snapshot

Linear fusion approach to convolutional neural networks for facial emotion recognition

inferred← citeshttps://doi.org/10.11591/ijra.v11i1.pp21-32openalex-snapshot

Recognizing facial emotions for educational learning settings

inferred← citeshttps://doi.org/10.1177/1059712316664017openalex-snapshot

Developing crossmodal expression recognition based on a deep neural model

inferred← citeshttps://doi.org/10.1186/s13640-015-0061-xopenalex-snapshot

A robust SVM classification framework using PSM for multi-class recognition

inferred← citeshttps://doi.org/10.1186/s13640-016-0140-7openalex-snapshot

Multithreading cascade of SURF for facial expression recognition

inferred← citeshttps://doi.org/10.14569/ijacsa.2018.090517openalex-snapshot

Classification of Affective States via EEG and Deep Learning

inferred← citeshttps://doi.org/10.14569/ijacsa.2020.0110137openalex-snapshot

Facial Emotion Recognition using Neighborhood Features

inferred← citeshttps://doi.org/10.1587/transinf.2019edl8038openalex-snapshot

Target-Adapted Subspace Learning for Cross-Corpus Speech Emotion Recognition

inferred← citeshttps://doi.org/10.1609/aaai.v31i1.10866openalex-snapshot

A Riemannian Network for SPD Matrix Learning

inferred← citeshttps://doi.org/10.1609/aaai.v32i1.11725openalex-snapshot

Building Deep Networks on Grassmann Manifolds

inferred← citeshttps://doi.org/10.1609/aaai.v33i01.33013215openalex-snapshot

Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition

inferred← citeshttps://doi.org/10.1609/aaai.v37i1.25077openalex-snapshot

Intensity-Aware Loss for Dynamic Facial Expression Recognition in the Wild

inferred← citeshttps://doi.org/10.18287/1613-0073-2017-1901-207-213openalex-snapshot

Compressing deep convolutional neural networks in visual emotion recognition

inferred← citeshttps://doi.org/10.18653/v1/w18-33openalex-snapshot

Proceedings of Grand Challenge and Workshop on Human Multimodal Language (Challenge-HML)

inferred← citeshttps://doi.org/10.19101/ijacr.2019.940117openalex-snapshot

Latest trends in emotion recognition methods: case study on emotiw challenge

inferred← citeshttps://doi.org/10.20381/ruor-23584openalex-snapshot

Multimodal Affective Computing Using Temporal Convolutional Neural Network and Deep Convolutional Neural Networks

inferred← citeshttps://doi.org/10.21437/interspeech.2015-569openalex-snapshot

Contemporary stochastic feature selection algorithms for speech-based emotion recognition

inferred← citeshttps://doi.org/10.21437/interspeech.2018-2360openalex-snapshot

Implementing Fusion Techniques for the Classification of Paralinguistic Information

inferred← citeshttps://doi.org/10.22266/ijies2021.0430.21openalex-snapshot

Engagement Detection through Facial Emotional Recognition Using a Shallow Residual Convolutional Neural Networks

inferred← citeshttps://doi.org/10.24963/ijcai.2021/413openalex-snapshot

Neural Architecture Search of SPD Manifold Networks

inferred← citeshttps://doi.org/10.25046/aj050638openalex-snapshot

Emotion Recognition on FER-2013 Face Images Using Fine-Tuned VGG-16

inferred← citeshttps://doi.org/10.26512/2016.03.d.20036openalex-snapshot

Como crianças reconhecem emoções em faces : o uso da variação da intensidade emocional

inferred← citeshttps://doi.org/10.32604/cmc.2024.046070openalex-snapshot

Facial Expression Recognition with High Response-Based Local Directional Pattern (HR-LDP) Network

inferred← citeshttps://doi.org/10.3390/electronics11081240openalex-snapshot

Real-Time Facial Expression Recognition Using Deep Learning with Application in the Active Classroom Environment

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