On the public citation graph

Multiple Spatio-temporal Feature Learning for Video-based Emotion Recognition in the Wild

https://doi.org/10.1145/3242969.3264992
0 signed · 99 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1016/j.neucom.2016.09.072openalex-snapshot
Funnel-structured cascade for multi-view face detection with alignment-awareness
inferredcites →https://doi.org/10.1016/j.neunet.2005.06.042openalex-snapshot
Framewise phoneme classification with bidirectional LSTM and other neural network architectures
inferredcites →https://doi.org/10.1016/j.patcog.2010.09.020openalex-snapshot
Survey on speech emotion recognition: Features, classification schemes, and databases
inferredcites →https://doi.org/10.1109/79.911197openalex-snapshot
Emotion recognition in human-computer interaction
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/iccv.2015.510openalex-snapshot
Learning Spatiotemporal Features with 3D Convolutional Networks
inferredcites →https://doi.org/10.1109/lsp.2016.2603342openalex-snapshot
Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks
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.2012.59openalex-snapshot
3D Convolutional Neural Networks for Human Action Recognition
inferredcites →https://doi.org/10.1126/science.270.5234.303openalex-snapshot
Speech Recognition with Primarily Temporal Cues
inferredcites →https://doi.org/10.1145/1873951.1874246openalex-snapshot
Opensmile
inferredcites →https://doi.org/10.1145/2522848.2531749openalex-snapshot
Emotion recognition in the wild challenge (EmotiW) challenge and workshop summary
inferredcites →https://doi.org/10.1145/2818346.2830596openalex-snapshot
Recurrent Neural Networks for Emotion Recognition in Video
inferredcites →https://doi.org/10.1145/2993148.2997630openalex-snapshot
Multi-clue fusion for emotion recognition in the wild
inferredcites →https://doi.org/10.1145/2993148.2997632openalex-snapshot
Video-based emotion recognition using CNN-RNN and C3D hybrid networks
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3136755.3143009openalex-snapshot
Learning supervised scoring ensemble for emotion recognition in the wild
inferredcites →https://doi.org/10.1145/3136755.3143011openalex-snapshot
Temporal multimodal fusion for video emotion classification in the wild
inferredcites →https://doi.org/10.1145/3242969.3264993openalex-snapshot
EmotiW 2018
inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot
Long Short-Term Memory
inferredcites →https://doi.org/10.21437/interspeech.2010-343openalex-snapshot
Recurrent neural network based language model
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1411.1792openalex-snapshot
How transferable are features in deep neural networks?
inferredcites →https://doi.org/10.48550/arxiv.1711.04598openalex-snapshot
Convolutional neural networks pretrained on large face recognition datasets for emotion classification from video
inferredcites →https://doi.org/10.5244/c.29.41openalex-snapshot
Deep Face Recognition

What points at this work

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

inferred← citeshttps://doi.org/10.2139/ssrn.4768851openalex-extracted
Noise-Reduced Dynamic Face Expression Identification with Frame-Level Attention and Global-Segment-Level Recognition
inferred← citeshttps://doi.org/10.1007/978-3-030-20518-8_28openalex-snapshot
Tandem Modelling Based Emotion Recognition in Videos
inferred← citeshttps://doi.org/10.1007/978-3-030-27202-9_29openalex-snapshot
Emotion Recognition with Spatial Attention and Temporal Softmax Pooling
inferred← citeshttps://doi.org/10.1007/978-3-030-31456-9_20openalex-snapshot
Cross-Dimension Transfer Learning for Video-Based Facial Expression Recognition
inferred← citeshttps://doi.org/10.1007/978-3-030-62362-3_18openalex-snapshot
One-Shot Only Real-Time Video Classification: A Case Study in Facial Emotion Recognition
inferred← citeshttps://doi.org/10.1007/978-3-030-66415-2_53openalex-snapshot
Noisy Student Training Using Body Language Dataset Improves Facial Expression Recognition
inferred← citeshttps://doi.org/10.1007/978-3-030-75418-1_29openalex-snapshot
Classification and Synthesis of Emotion in Sign Languages Using Neutral Expression Deviation Factor and 4D Trajectories
inferred← citeshttps://doi.org/10.1007/978-3-031-83790-6_23openalex-snapshot
CRNet: Convolutive Recurrent Network for Suspect Face Identification
inferred← citeshttps://doi.org/10.1007/978-3-032-13075-4_4openalex-snapshot
Towards Facial Expression Analysis for Enhanced Threat Detection in Surveillance
inferred← citeshttps://doi.org/10.1007/978-981-97-5146-4_24openalex-snapshot
³Comparative Analysis of Audio–Video Multimodal Methods for Emotion Recognition
inferred← citeshttps://doi.org/10.1007/s00530-023-01248-xopenalex-snapshot
A defensive attention mechanism to detect deepfake content across multiple modalities
inferred← citeshttps://doi.org/10.1007/s10489-026-07195-0openalex-snapshot
DAMT-Former: Dynamic Attention and Multi-scale Temporal Former for Facial Expression Recognition
inferred← citeshttps://doi.org/10.1007/s11042-020-10203-1openalex-snapshot
User-generated video emotion recognition based on key frames
inferred← citeshttps://doi.org/10.1007/s11042-022-13559-8openalex-snapshot
The limitations for expression recognition in computer vision introduced by facial masks
inferred← citeshttps://doi.org/10.1007/s11042-023-14491-1openalex-snapshot
Facial emotion recognition on video using deep attention based bidirectional LSTM with equilibrium optimizer
inferred← citeshttps://doi.org/10.1007/s12559-026-10548-zopenalex-snapshot
CLVSR: Concept-Guided Language-Visual Feature Learning and Sample Rebalance for Dynamic Facial Expression Recognition
inferred← citeshttps://doi.org/10.1007/s44443-026-00511-1openalex-snapshot
STAR-Former: spatio-temporal adaptive and region-aware transformer for dynamic facial expression recognition
inferred← citeshttps://doi.org/10.1016/j.asoc.2024.111680openalex-snapshot
A joint local spatial and global temporal CNN-Transformer for dynamic facial expression recognition
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.123635openalex-snapshot
Multi-geometry embedded transformer for facial expression recognition in videos
inferred← citeshttps://doi.org/10.1016/j.neucom.2019.06.046openalex-snapshot
Affective question answering on video
inferred← citeshttps://doi.org/10.1016/j.neucom.2019.11.127openalex-snapshot
Multi-attention based Deep Neural Network with hybrid features for Dynamic Sequential Facial Expression Recognition
inferred← citeshttps://doi.org/10.1016/j.neucom.2020.06.062openalex-snapshot
SAANet: Siamese action-units attention network for improving dynamic facial expression recognition
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.130020openalex-snapshot
Dynamic facial expression recognition in the wild via Multi-Snippet Spatiotemporal Learning
inferred← citeshttps://doi.org/10.1016/j.neunet.2024.106573openalex-snapshot
CDGT: Constructing diverse graph transformers for emotion recognition from facial videos
inferred← citeshttps://doi.org/10.1016/j.patcog.2021.108105openalex-snapshot
Mutual information regularized identity-aware facial expression recognition in compressed video
inferred← citeshttps://doi.org/10.1109/acii.2019.8925445openalex-snapshot
A Deep Framework for Facial Emotion Recognition using Light Field Images
inferred← citeshttps://doi.org/10.1109/acii52823.2021.9597460openalex-snapshot
Spatiotemporal Contrastive Learning of Facial Expressions in Videos
inferred← citeshttps://doi.org/10.1109/acii59096.2023.10388146openalex-snapshot
A Weakly Supervised Approach to Emotion-change Prediction and Improved Mood Inference
inferred← citeshttps://doi.org/10.1109/cvpr52729.2023.01722openalex-snapshot
Rethinking the Learning Paradigm for Dynamic Facial Expression Recognition
inferred← citeshttps://doi.org/10.1109/cvprw59228.2023.00602openalex-snapshot
Frame Level Emotion Guided Dynamic Facial Expression Recognition with Emotion Grouping
inferred← citeshttps://doi.org/10.1109/globalsip45357.2019.8969360openalex-snapshot
Extracting Audio-Visual Features for Emotion Recognition Through Active Feature Selection
inferred← citeshttps://doi.org/10.1109/icassp40776.2020.9053919openalex-snapshot
Facial Emotion Recognition Using Light Field Images with Deep Attention-Based Bidirectional LSTM
inferred← citeshttps://doi.org/10.1109/icassp55912.2026.11462009openalex-snapshot
D2M: Decoupling to Modulate via Emotion Trajectories for Dynamic Facial Expression Recognition
inferred← citeshttps://doi.org/10.1109/iccims61672.2024.10690812openalex-snapshot
A cheating detection system in online exams through real-time facial emotion recognition of students
inferred← citeshttps://doi.org/10.1109/iccvw.2019.00464openalex-snapshot
Audio-Video Based Emotion Recognition Using Minimum Cost Flow Algorithm
inferred← citeshttps://doi.org/10.1109/icpr48806.2021.9413094openalex-snapshot
Video-based Facial Expression Recognition using Graph Convolutional Networks
inferred← citeshttps://doi.org/10.1109/idaacs.2019.8924297openalex-snapshot
Twosome Modelling based Emotion Recognition in Videos
inferred← citeshttps://doi.org/10.1109/inocon60754.2024.10512101openalex-snapshot
Facial Expression Recognition in Video Using 3D-CNN Deep Features Discrimination
inferred← citeshttps://doi.org/10.1109/ssd.2019.8893159openalex-snapshot
Subject-Independent Multi-Domain Facial Emotion Recognition with Local Salient Features
inferred← citeshttps://doi.org/10.1109/taffc.2021.3095425openalex-snapshot
Modeling Multiple Temporal Scales of Full-Body Movements for Emotion Classification
inferred← citeshttps://doi.org/10.1109/taffc.2022.3181736openalex-snapshot
Spatial-Temporal Graphs Plus Transformers for Geometry-Guided Facial Expression Recognition
inferred← citeshttps://doi.org/10.1109/taffc.2025.3530973openalex-snapshot
Modeling Fine-Grained Relations in Dynamic Space-Time Graphs for Video-Based Facial Expression Recognition
inferred← citeshttps://doi.org/10.1109/taslp.2021.3096037openalex-snapshot
Information Fusion in Attention Networks Using Adaptive and Multi-Level Factorized Bilinear Pooling for Audio-Visual Emotion Recognition
inferred← citeshttps://doi.org/10.1109/tbiom.2025.3546279openalex-snapshot
Robust Dynamic Facial Expression Recognition
inferred← citeshttps://doi.org/10.1109/tcsvt.2022.3182658openalex-snapshot
Selective Element and Two Orders Vectorization Networks for Automatic Depression Severity Diagnosis via Facial Changes
inferred← citeshttps://doi.org/10.1109/tcsvt.2024.3450652openalex-snapshot
CFAN-SDA: Coarse-Fine Aware Network With Static-Dynamic Adaptation for Facial Expression Recognition in Videos
inferred← citeshttps://doi.org/10.1109/tetci.2021.3070713openalex-snapshot
Attend to Where and When: Cascaded Attention Network for Facial Expression Recognition
inferred← citeshttps://doi.org/10.1109/tmm.2024.3407693openalex-snapshot
Label-Guided Dynamic Spatial-Temporal Fusion for Video-Based Facial Expression Recognition
inferred← citeshttps://doi.org/10.1109/ubmk.2019.8907100openalex-snapshot
Emotion Prediction in Movies Using Visual Features & Genre Information
inferred← citeshttps://doi.org/10.1109/wacv48630.2021.00307openalex-snapshot
Temporal Stochastic Softmax for 3D CNNs: An Application in Facial Expression Recognition
inferred← citeshttps://doi.org/10.1145/3242969.3264993openalex-snapshot
EmotiW 2018
inferred← citeshttps://doi.org/10.1145/3340555.3355713openalex-snapshot
Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition
inferred← citeshttps://doi.org/10.1145/3340555.3355720openalex-snapshot
Multi-Attention Fusion Network for Video-based Emotion Recognition
inferred← citeshttps://doi.org/10.1145/3394171.3413620openalex-snapshot
DFEW
inferred← citeshttps://doi.org/10.1145/3474085.3475292openalex-snapshot
Former-DFER: Dynamic Facial Expression Recognition Transformer
inferred← citeshttps://doi.org/10.1145/3503161.3547865openalex-snapshot
DPCNet: Dual Path Multi-Excitation Collaborative Network for Facial Expression Representation Learning in Videos
inferred← citeshttps://doi.org/10.1145/3503161.3548373openalex-snapshot
Learning from Label Relationships in Human Affect
inferred← citeshttps://doi.org/10.1145/3508546.3508581openalex-snapshot
Learning Dynamics for Video Facial Expression Recognition
inferred← citeshttps://doi.org/10.1145/3581783.3611972openalex-snapshot
Freq-HD: An Interpretable Frequency-based High-Dynamics Affective Clip Selection Method for in-the-Wild Facial Expression Recognition in Videos
inferred← citeshttps://doi.org/10.1145/3664647.3681583openalex-snapshot
Open-Set Video-based Facial Expression Recognition with Human Expression-sensitive Prompting
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/10.21014/acta_imeko.v11i2.1174openalex-snapshot
Video-based emotion sensing and recognition using convolutional neural network based kinetic gas molecule optimization
inferred← citeshttps://doi.org/10.3390/e24081046openalex-snapshot
Progressively Discriminative Transfer Network for Cross-Corpus Speech Emotion Recognition
inferred← citeshttps://doi.org/10.3390/s20185184openalex-snapshot
Visual Scene-Aware Hybrid and Multi-Modal Feature Aggregation for Facial Expression Recognition
inferred← citeshttps://doi.org/10.3390/s21072344openalex-snapshot
Context-Aware Emotion Recognition in the Wild Using Spatio-Temporal and Temporal-Pyramid Models
inferred← citeshttps://doi.org/10.3390/s23041834openalex-snapshot
Multimodal Sensor-Input Architecture with Deep Learning for Audio-Visual Speech Recognition in Wild
inferred← citeshttps://doi.org/10.3390/s25123829openalex-snapshot
Res-RBG Facial Expression Recognition in Image Sequences Based on Dual Neural Networks
inferred← citeshttps://doi.org/10.3390/sym14040687openalex-snapshot
Driver Emotions Recognition Based on Improved Faster R-CNN and Neural Architectural Search Network
inferred← citeshttps://doi.org/10.36224/ijes.150104openalex-snapshot
DepressNet: A Multimodal Hierarchical Attention Mechanism approach for Depression Detection
inferred← citeshttps://doi.org/10.48550/arxiv.1808.07773openalex-snapshot
EmotiW 2018: Audio-Video, Student Engagement and Group-Level Affect Prediction
inferred← citeshttps://doi.org/10.48550/arxiv.1911.05187openalex-snapshot
AI in Pursuit of Happiness, Finding Only Sadness: Multi-Modal Facial Emotion Recognition Challenge
inferred← citeshttps://doi.org/10.48550/arxiv.2111.08910openalex-snapshot
Information Fusion in Attention Networks Using Adaptive and Multi-level Factorized Bilinear Pooling for Audio-visual Emotion Recognition
inferred← citeshttps://doi.org/10.53759/7669/jmc202505122openalex-snapshot
Adaptive Firefly Optimization Based Feature Selection and Ensemble Machine Learning Algorithm for Facial Expression Emotion Recognition
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.