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Learning active facial patches for expression analysis

https://doi.org/10.1109/cvpr.2012.6247974

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What this work says

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

inferredcites →https://doi.org/10.1007/s10994-007-5040-8openalex-snapshot

Convex multi-task feature learning

inferredcites →https://doi.org/10.1016/j.imavis.2008.08.005openalex-snapshot

Facial expression recognition based on Local Binary Patterns: A comprehensive study

inferredcites →https://doi.org/10.1016/j.imavis.2008.11.007openalex-snapshot

Social signal processing: Survey of an emerging domain

inferredcites →https://doi.org/10.1017/9781316676202openalex-snapshot

Social Signal Processing

inferredcites →https://doi.org/10.1023/a:1007379606734openalex-snapshot

Multitask Learning

inferredcites →https://doi.org/10.1023/b:visi.0000013087.49260.fbopenalex-snapshot

Robust Real-Time Face Detection

inferredcites →https://doi.org/10.1037/t27734-000openalex-snapshot

Facial Action Coding System

inferredcites →https://doi.org/10.1109/34.817413openalex-snapshot

Automatic classification of single facial images

inferredcites →https://doi.org/10.1109/afgr.2000.840611openalex-snapshot

Comprehensive database for facial expression analysis

inferredcites →https://doi.org/10.1109/afgr.2000.840678openalex-snapshot

Recognizing lower face action units for facial expression analysis

inferredcites →https://doi.org/10.1109/ccst.2009.5335546openalex-snapshot

Automated Facial Expression Recognition System

inferredcites →https://doi.org/10.1109/cvpr.2000.855832openalex-snapshot

Recognizing upper face action units for facial expression analysis

inferredcites →https://doi.org/10.1109/cvpr.2004.327openalex-snapshot

Dynamics of Facial Expression Extracted Automatically from Video

inferredcites →https://doi.org/10.1109/cvpr.2004.334openalex-snapshot

Evaluation of Face Resolution for Expression Analysis

inferredcites →https://doi.org/10.1109/cvpr.2005.297openalex-snapshot

Recognizing Facial Expression: Machine Learning and Application to Spontaneous Behavior

inferredcites →https://doi.org/10.1109/cvpr.2009.5206736openalex-snapshot

Boosted multi-task learning for face verification with applications to web image and video search

inferredcites →https://doi.org/10.1109/cvpr.2010.5539967openalex-snapshot

Visual classification with multi-task joint sparse representation

inferredcites →https://doi.org/10.1109/cvpr.2010.5539978openalex-snapshot

Exploring facial expressions with compositional features

inferredcites →https://doi.org/10.1109/cvpr.2010.5540036openalex-snapshot

Automatic image annotation using group sparsity

inferredcites →https://doi.org/10.1109/cvprw.2009.5206736openalex-snapshot

Boosted multi-task learning for face verification with applications to web image and video search

inferredcites →https://doi.org/10.1109/fgr.2006.61openalex-snapshot

Haar Features for FACS AU Recognition

inferredcites →https://doi.org/10.1109/icdm.2009.128openalex-snapshot

Accelerated Gradient Method for Multi-task Sparse Learning Problem

inferredcites →https://doi.org/10.1109/tpami.2002.1017623openalex-snapshot

Multiresolution gray-scale and rotation invariant texture classification with local binary patterns

inferredcites →https://doi.org/10.1109/tpami.2007.1094openalex-snapshot

Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships

inferredcites →https://doi.org/10.1109/tsmcb.2011.2179533openalex-snapshot

Automatic Image Annotation and Retrieval Using Group Sparsity

inferredcites →https://doi.org/10.1145/1835804.1835952openalex-snapshot

Learning incoherent sparse and low-rank patterns from multiple tasks

inferredcites →https://doi.org/10.1145/2086737.2086742openalex-snapshot

Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks

inferredcites →https://doi.org/10.7551/mitpress/7503.003.0010openalex-snapshot

Multi-Task Feature Learning

What points at this work

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

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Micro‐ and Macro‐Expression Analysis

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Multilayer‐neighbor local binary pattern for facial expression recognition

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Facial Expression Recognition and Analysis of Interclass False Positives Using CNN

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Action Unit Assisted Facial Expression Recognition

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The Riemannian and Affine Geometry of Facial Expression and Action Recognition

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Multi-pose Facial Expression Recognition Based on Unpaired Images

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Occlusion-Aware Facial Expression Recognition Based Region Re-weight Network

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Facial Expression Recognition from Occluded Images Using Deep Convolution Neural Network with Vision Transformer

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MDDAMFN: Mixed Dual-Direction Attention Mechanism to Enhance Facial Expression

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Feature Disentangling Machine - A Novel Approach of Feature Selection and Disentangling in Facial Expression Analysis

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Multi-instance Feature Learning Based on Sparse Representation for Facial Expression Recognition

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Monte Carlo Based Importance Estimation of Localized Feature Descriptors for the Recognition of Facial Expressions

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Effective Facial Expression Recognition via the Boosted Convolutional Neural Network

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Distance Signature for Recognizing Human Emotions

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Texture Signature for Recognizing Human Emotions

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Distance-Shape Signature Duo for Determination of Human Emotion

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Distance-Texture Signature Duo for Determination of Human Emotion

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Human Emotion Recognition from Distance-Shape-Texture Signature Trio

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Joint Pose and Expression Modeling for Facial Expression Recognition

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Label Distribution Learning on Auxiliary Label Space Graphs for Facial Expression Recognition

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Subject Adaptive Affection Recognition via Sparse Reconstruction

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FATAUVA-Net: An Integrated Deep Learning Framework for Facial Attribute Recognition, Action Unit Detection, and Valence-Arousal Estimation

inferred← citeshttps://doi.org/10.1109/ddcls61622.2024.10606687openalex-snapshot

Exploring New Frontiers in Facial Expression Recognition: Dual DenseNet-201 and Landmark Distance Analytics in the Wild

inferred← citeshttps://doi.org/10.1109/desec.2017.8073838openalex-snapshot

SVM point-based real-time emotion detection

inferred← citeshttps://doi.org/10.1109/fg.2013.6553734openalex-snapshot

AU-aware Deep Networks for facial expression recognition

inferred← citeshttps://doi.org/10.1109/fg.2013.6553774openalex-snapshot

Improving facial expression analysis using histograms of Log-Transformed Nonnegative Sparse Representation with a Spatial Pyramid Structure

inferred← citeshttps://doi.org/10.1109/fg.2015.7163081openalex-snapshot

Exploiting sparsity and co-occurrence structure for action unit recognition

inferred← citeshttps://doi.org/10.1109/fg.2015.7284872openalex-snapshot

Learning to combine local models for facial Action Unit detection

inferred← citeshttps://doi.org/10.1109/fg.2017.13openalex-snapshot

Learning Spatial and Temporal Cues for Multi-Label Facial Action Unit Detection

inferred← citeshttps://doi.org/10.1109/fg.2017.144openalex-snapshot

Sayette Group Formation Task (GFT) Spontaneous Facial Expression Database

inferred← citeshttps://doi.org/10.1109/fg.2017.23openalex-snapshot

FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition

inferred← citeshttps://doi.org/10.1109/fg.2019.8756580openalex-snapshot

Expression Empowered ResiDen Network for Facial Action Unit Detection

inferred← citeshttps://doi.org/10.1109/fg.2019.8756596openalex-snapshot

Generalizing to Unseen Head Poses in Facial Expression Recognition and Action Unit Intensity Estimation

inferred← citeshttps://doi.org/10.1109/fg.2019.8756615openalex-snapshot

A Graph-Structured Representation with BRNN for Static-based Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/fg.2019.8756631openalex-snapshot

IdenNet: Identity-Aware Facial Action Unit Detection

inferred← citeshttps://doi.org/10.1109/fg47880.2020.00110openalex-snapshot

CLIFER: Continual Learning with Imagination for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/fg52635.2021.9666935openalex-snapshot

Two-stream Gabor-AGraph Convolutional Networks for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/fg52635.2021.9667034openalex-snapshot

Contextual Emotion Learning Challenge

inferred← citeshttps://doi.org/10.1109/ftc.2016.7821710openalex-snapshot

Multimodal architecture for emotion in robots using deep learning

inferred← citeshttps://doi.org/10.1109/icaibd64986.2025.11081988openalex-snapshot

ER-EDF: An Enhanced Real-Time Emotion Detection Framework for Edge Devices in Emotional Robotics

inferred← citeshttps://doi.org/10.1109/icalt.2017.135openalex-snapshot

Creation of a Facial Expression Corpus from EEG Signals for Learning Centered Emotions

inferred← citeshttps://doi.org/10.1109/icassp.2014.6854261openalex-snapshot

Sparse localized facial motion dictionary learning for facial expression recognition

inferred← citeshttps://doi.org/10.1109/icassp.2015.7178983openalex-snapshot

Leveraging valence and activation information via multi-task learning for categorical emotion recognition

inferred← citeshttps://doi.org/10.1109/icatcct.2016.7912070openalex-snapshot

Human Facial Expression Recognition from static images using shape and appearance feature

inferred← citeshttps://doi.org/10.1109/iccasit50869.2020.9368700openalex-snapshot

Low-Resolution Facial Expression Recognition Based on Texture Mapping-Based GcForest

inferred← citeshttps://doi.org/10.1109/iccc51575.2020.9345019openalex-snapshot

Pose-Robust Facial Expression Recognition by 3D Morphable Model Learning

inferred← citeshttps://doi.org/10.1109/icccnt56998.2023.10308392openalex-snapshot

FERLP: Facial Emotion Recognition Based on Landmark Points using Artificial Intelligence and Machine Learning

inferred← citeshttps://doi.org/10.1109/iccnea50255.2020.00025openalex-snapshot

Research on Facial Expression Recognition Based on Neural Network

inferred← citeshttps://doi.org/10.1109/iccubea58933.2023.10392279openalex-snapshot

Estimation of Facial Emotion Based on Landmark Points by Applying Artificial Intelligence and Machine Learning

inferred← citeshttps://doi.org/10.1109/iccv.2013.298openalex-snapshot

Facial Action Unit Event Detection by Cascade of Tasks

inferred← citeshttps://doi.org/10.1109/iccv.2015.341openalex-snapshot

Joint Fine-Tuning in Deep Neural Networks for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/iccv.2015.430openalex-snapshot

Learning to Transfer: Transferring Latent Task Structures and Its Application to Person-Specific Facial Action Unit Detection

inferred← citeshttps://doi.org/10.1109/iccv.2017.345openalex-snapshot

A Novel Space-Time Representation on the Positive Semidefinite Cone for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/iccv.2019.01024openalex-snapshot

Context-Aware Emotion Recognition Networks

inferred← citeshttps://doi.org/10.1109/iccvw.2015.12openalex-snapshot

Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition?

inferred← citeshttps://doi.org/10.1109/iccvw.2015.13openalex-snapshot

FaceCept3D: Real Time 3D Face Tracking and Analysis

inferred← citeshttps://doi.org/10.1109/iccvw.2015.76openalex-snapshot

Automatic Emotion Recognition in Robot-Children Interaction for ASD Treatment

inferred← citeshttps://doi.org/10.1109/iccvw.2017.166openalex-snapshot

A Computer Vision Based Approach for Understanding Emotional Involvements in Children with Autism Spectrum Disorders

inferred← citeshttps://doi.org/10.1109/iccvw.2017.189openalex-snapshot

Using Synthetic Data to Improve Facial Expression Analysis with 3D Convolutional Networks

inferred← citeshttps://doi.org/10.1109/iccvw60793.2023.00339openalex-snapshot

POSTER: A Pyramid Cross-Fusion Transformer Network for Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/icet.2015.7389223openalex-snapshot

Facial expression recognition using two-tier classification and its application to smart home automation system

inferred← citeshttps://doi.org/10.1109/icet.2017.8281753openalex-snapshot

Using deep autoencoders for facial expression recognition

inferred← citeshttps://doi.org/10.1109/icip.2013.6738246openalex-snapshot

Discriminative filter based regression learning for facial expression recognition

inferred← citeshttps://doi.org/10.1109/icip.2014.7026206openalex-snapshot

Online facial expression recognition based on combining texture and geometric information

inferred← citeshttps://doi.org/10.1109/icip.2017.8296590openalex-snapshot

A statistic manifold kernel with graph embedding discriminant analysis for action and expression recognition

inferred← citeshttps://doi.org/10.1109/iciteed.2017.8250446openalex-snapshot

Facial expression recognition using local Gabor filters and PCA plus LDA

inferred← citeshttps://doi.org/10.1109/icme.2013.6607638openalex-snapshot

Seeing through the expression: Bridging the gap between expression and emotion recognition

inferred← citeshttps://doi.org/10.1109/icmlc.2016.7872938openalex-snapshot

Facial expression recognition based on salient patch selection

inferred← citeshttps://doi.org/10.1109/icmlc48188.2019.8949236openalex-snapshot

Facial Expression Based Emotion Recognition Employing YOLOv3 Deep Neural Networks

inferred← citeshttps://doi.org/10.1109/icoei.2017.8300838openalex-snapshot

Automatic recognition of facial expression using features of salient patches with SVM and ANN classifier

inferred← citeshttps://doi.org/10.1109/icosec61587.2024.10722685openalex-snapshot

Facial Expression Analysis using K-Nearest Neighbor Classification Method: Enhancing Emotion Detection and Stress Monitoring in an Interactive Music Player

inferred← citeshttps://doi.org/10.1109/icpr.2014.80openalex-snapshot

A Local Approach for Negative Emotion Detection

inferred← citeshttps://doi.org/10.1109/icpr.2016.7900279openalex-snapshot

Facial expression recognition by re-ranking with global and local generic features

inferred← citeshttps://doi.org/10.1109/icpr.2018.8545596openalex-snapshot

Dynamic Facial Expression Recognition Based on Convolutional Neural Networks with Dense Connections

inferred← citeshttps://doi.org/10.1109/icpr.2018.8545725openalex-snapshot

Facial Expression Recognition for Different Pose Faces Based on Special Landmark Detection

inferred← citeshttps://doi.org/10.1109/icpr.2018.8545853openalex-snapshot

Patch-Gated CNN for Occlusion-aware Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/icra40945.2020.9197547openalex-snapshot

Natural Scene Facial Expression Recognition with Dimension Reduction Network

inferred← citeshttps://doi.org/10.1109/icrss67786.2025.00058openalex-snapshot

Investigating Performance-Efficiency Trade-Offs in Lightweight Facial Expression Recognition Models

inferred← citeshttps://doi.org/10.1109/icst59744.2023.10460799openalex-snapshot

Sensory Maze: A camera-based remote expression therapy interface

inferred← citeshttps://doi.org/10.1109/iemcon.2016.7746266openalex-snapshot

Size variant landmark patches for Facial Action Unit detection

inferred← citeshttps://doi.org/10.1109/ijcb48548.2020.9304923openalex-snapshot

Occlusion-Adaptive Deep Network for Robust Facial Expression Recognition

inferred← citeshttps://doi.org/10.1109/ijcnn.2017.7966100openalex-snapshot

Action unit selective feature maps in deep networks for facial expression recognition

inferred← citeshttps://doi.org/10.1109/ijcnn.2018.8489415openalex-snapshot

Extended LBP based Facial Expression Recognition System for Adaptive AI Agent Behaviour

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