Search Results for author:
Found 7 papers, 6 papers with code
Linguistic-Based Mild Cognitive Impairment Detection Using Informative Loss
Our proposed NLP framework consists of two Transformer-based modules, namely Sentence Embedding (SE) and Sentence Cross Attention (SCA).
GANalyzer: Analysis and Manipulation of GANs Latent Space for Controllable Face Synthesis
We analyze facial attribute entanglement in the latent space of GANs and apply the proposed transformation for editing the disentangled facial attributes.
ACR Loss: Adaptive Coordinate-based Regression Loss for Face Alignment
Heatmap-based Regression (HBR) and Coordinate-based Regression (CBR) are among the two mainly used methods for face alignment.
Ranked #14 on
Face Alignment
on COFW
Ad-Corre: Adaptive Correlation-Based Loss for Facial Expression Recognition in the Wild
In addition, the Mean Discriminator component leads the network to make the mean embedded feature vectors of different classes to be less similar to each other. We use Xception network as the backbone of our model, and contrary to previous work, we propose an embedding feature space that contains k feature vectors.
Ranked #10 on
Facial Expression Recognition (FER)
on FER2013
Facial Expression Recognition
Facial Expression Recognition (FER)
+1
XnODR and XnIDR: Two Accurate and Fast Fully Connected Layers For Convolutional Neural Networks
To address the computational burdens of the Dynamic Routing mechanism, this paper proposes new Fully Connected (FC) layers by xnorizing the linear projection outside or inside the Dynamic Routing within the CapsFC layer.
Ranked #11 on
Image Classification
on MNIST
(Accuracy metric)
Facial Landmark Points Detection Using Knowledge Distillation-Based Neural Networks
We use two Teacher networks, a Tolerant-Teacher and a Tough-Teacher in conjunction with the Student network.
Ranked #17 on
Face Alignment
on COFW
ASMNet: a Lightweight Deep Neural Network for Face Alignment and Pose Estimation
We compare the performance of our proposed model called ASMNet with MobileNetV2 (which is about 2 times bigger than ASMNet) in both the face alignment and pose estimation tasks.
Ranked #1 on
Head Pose Estimation
on COFW
