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Dynamic Facial Expression Recognition

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Showing 1–42 of 42 papers

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