3D Facial Expression Recognition
2개 벤치마크 · 논문 13편 · 이 태스크의 논문 보기 →
Benchmarks
!(()&&!|*|*|
2017_test set
Most implemented
Emotion estimation from video footage with LSTM
ExpNet: Landmark-Free, Deep, 3D Facial Expressions
Papers
Emotion estimation from video footage with LSTM
Emotion estimation in general is a field that has been studied for a long time, and several approaches exist using machine learning. in this paper, we present an LSTM model, that processes the blend-shapes produced by th…
3D Facial Expression RecognitionDrFER: Learning Disentangled Representations for 3D Facial Expression Recognition
Facial Expression Recognition (FER) has consistently been a focal point in the field of facial analysis. In the context of existing methodologies for 3D FER or 2D+3D FER, the extraction of expression features often gets …
3D Facial Expression RecognitionDisentanglementFacial Expression RecognitionFacial Expression Recognition (FER)+10/1 Deep Neural Networks via Block Coordinate Descent
The step function is one of the simplest and most natural activation functions for deep neural networks (DNNs). As it counts 1 for positive variables and 0 for others, its intrinsic characteristics (e.g., discontinuity a…
10-shot image generation16k2D Object Detection+92AFNet-M: Adaptive Fusion Network with Masks for 2D+3D Facial Expression Recognition
2D+3D facial expression recognition (FER) can effectively cope with illumination changes and pose variations by simultaneously merging 2D texture and more robust 3D depth information. Most deep learning-based approaches …
3D Facial Expression RecognitionFacial Expression RecognitionFacial Expression Recognition (FER)2D+3D facial expression recognition via embedded tensor manifold regularization
In this paper, a novel approach via embedded tensor manifold regularization for 2D+3D facial expression recognition (FERETMR) is proposed. Firstly, 3D tensors are constructed from 2D face images and 3D face shape models …
3D Facial Expression RecognitionDimensionality ReductionFacial Expression RecognitionFacial Expression Recognition (FER)MFEViT: A Robust Lightweight Transformer-based Network for Multimodal 2D+3D Facial Expression Recognition
Vision transformer (ViT) has been widely applied in many areas due to its self-attention mechanism that help obtain the global receptive field since the first layer. It even achieves surprising performance exceeding CNN …
3D Facial Expression RecognitionFacial Expression RecognitionFacial Expression Recognition (FER)