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Dynamic Facial Expression Recognition

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Showing 1–42 of 42 papers

TitleStatusHype
Deep Residual Learning for Image RecognitionCode4
Learning Spatiotemporal Features with 3D Convolutional NetworksCode2
MMA-DFER: MultiModal Adaptation of unimodal models for Dynamic Facial Expression Recognition in-the-wildCode2
HiCMAE: Hierarchical Contrastive Masked Autoencoder for Self-Supervised Audio-Visual Emotion RecognitionCode2
Robust Dynamic Facial Expression RecognitionCode2
Intensity-Aware Loss for Dynamic Facial Expression Recognition in the WildCode1
Former-DFER: Dynamic Facial Expression Recognition TransformerCode1
MAE-DFER: Efficient Masked Autoencoder for Self-supervised Dynamic Facial Expression RecognitionCode1
From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in VideosCode1
Prompting Visual-Language Models for Dynamic Facial Expression RecognitionCode1
SVFAP: Self-supervised Video Facial Affect PerceiverCode1
Static for Dynamic: Towards a Deeper Understanding of Dynamic Facial Expressions Using Static Expression DataCode1
VAEmo: Efficient Representation Learning for Visual-Audio Emotion with Knowledge InjectionCode0
Rethinking the Learning Paradigm for Dynamic Facial Expression RecognitionCode0
Lifting Scheme-Based Implicit Disentanglement of Emotion-Related Facial Dynamics in the WildCode0
Clip-aware expressive feature learning for video-based facial expression recognitionCode0
EmojiHeroVR: A Study on Facial Expression Recognition under Partial Occlusion from Head-Mounted DisplaysCode0
MTCAE-DFER: Multi-Task Cascaded Autoencoder for Dynamic Facial Expression RecognitionCode0
FRU-Adapter: Frame Recalibration Unit Adapter for Dynamic Facial Expression RecognitionCode0
PE-CLIP: A Parameter-Efficient Fine-Tuning of Vision Language Models for Dynamic Facial Expression RecognitionCode0
D2SP: Dynamic Dual-Stage Purification Framework for Dual Noise Mitigation in Vision-based Affective Recognition—0
Spatio-Temporal Transformer for Dynamic Facial Expression Recognition in the Wild—0
MAFW: A Large-scale, Multi-modal, Compound Affective Database for Dynamic Facial Expression Recognition in the Wild—0
A^3lign-DFER: Pioneering Comprehensive Dynamic Affective Alignment for Dynamic Facial Expression Recognition with CLIP—0
All rivers run into the sea: Unified Modality Brain-like Emotional Central Mechanism—0
CLIPER: A Unified Vision-Language Framework for In-the-Wild Facial Expression Recognition—0
D2SP: Dynamic Dual-Stage Purification Framework for Dual Noise Mitigation in Vision-based Affective Recognition.—0
DFEW: A Large-Scale Database for Recognizing Dynamic Facial Expressions in the Wild—0
DPCNet: Dual Path Multi-Excitation Collaborative Network for Facial Expression Representation Learning in Videos—0
Dynamic Facial Expression Recognition under Partial Occlusion with Optical Flow Reconstruction—0
Enhancing Ambiguous Dynamic Facial Expression Recognition with Soft Label-based Data Augmentation—0
Expression Snippet Transformer for Robust Video-based Facial Expression Recognition—0
FineCLIPER: Multi-modal Fine-grained CLIP for Dynamic Facial Expression Recognition with AdaptERs—0
Human Expression Recognition using Facial Shape Based Fourier Descriptors Fusion—0
Learning Expressionlets on Spatio-Temporal Manifold for Dynamic Facial Expression Recognition—0
Learning Expressionlets via Universal Manifold Model for Dynamic Facial Expression Recognition—0
LOGO-Former: Local-Global Spatio-Temporal Transformer for Dynamic Facial Expression Recognition—0
FE-Adapter: Adapting Image-based Emotion Classifiers to Videos—0
MIDAS: Mixing Ambiguous Data with Soft Labels for Dynamic Facial Expression Recognition—0
MSSTNet: A Multi-Scale Spatio-Temporal CNN-Transformer Network for Dynamic Facial Expression Recognition—0
NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition—0
OUS: Scene-Guided Dynamic Facial Expression Recognition—0
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