ResMaskNet is a convolutional neural network that combines residual masking mechanisms with a U-Net architecture for facial emotion recognition.

A facial expression recognition model based on ViT architecture, fine-tuned on the imagefolder dataset with an accuracy of 91.77%

Computer VisionTransformers

A facial expression recognition model fine-tuned based on a pre-trained model, which can effectively recognize eight different facial expressions.

Computer VisionTransformers

A ViT-based facial expression recognition model fine-tuned on FER2013, MMI, and AffectNet datasets, capable of recognizing seven basic emotions

Computer VisionTransformers

ViT-based facial expression recognition model, fine-tuned on FER2013, MMI, and AffectNet datasets, supporting seven emotion classifications

Computer VisionTransformers

IP-Adapter-FaceID is a face recognition-based text-to-image generation model capable of generating various styles of images based on facial ID embeddings.

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A facial emotion recognition model fine-tuned based on Google's ViT-base model, achieving 91% accuracy on the test set.

Computer VisionTransformers

An image classification model based on ViT architecture, fine-tuned on the FER2013 dataset for facial expression recognition tasks.

Computer VisionTransformers

A facial expression recognition model fine-tuned based on Google's ViT model, trained on the FER2013 dataset with an accuracy of 70.22%.

Computer VisionTransformers

A vision model fine-tuned from google/vit-base-patch16-224-in21k for facial expression recognition tasks

Computer VisionTransformers

A facial expression recognition model fine-tuned based on Microsoft BEiT, achieving 68.6% accuracy on the FER dataset

Computer VisionTransformers

Facial expression recognition model fine-tuned based on ResNet-50 architecture, trained on FER2013 and CKPlus datasets

Computer VisionTransformers

A facial expression recognition model fine-tuned based on the ResNet-50 architecture, trained on the FER2013 and CK+ datasets, achieving an accuracy of 1.0

Computer VisionTransformers

A vision Transformer model based on the BEiT architecture, fine-tuned on FER2013CKPlus and SFEW datasets for facial expression recognition tasks.

Computer VisionTransformers

An image classification model based on the BEiT architecture, fine-tuned on the FER2013 and CK+ datasets, primarily used for facial expression recognition tasks.

Computer VisionTransformers

A facial expression recognition model fine-tuned based on the ResNet-50 architecture, trained on the FER2013 dataset with an accuracy of 68.47%

Computer VisionTransformers

An image classification model based on the BEiT architecture, fine-tuned on the FER2013 dataset for facial expression recognition

Computer VisionTransformers

This is an image classification model based on the BEiT architecture, fine-tuned on the FER2013 and CK+ datasets for facial expression recognition tasks.

Computer VisionTransformers

This model is an image classification model based on the BEiT architecture, fine-tuned on the FER2013CKPlus dataset for facial expression recognition tasks.

Computer VisionTransformers

Facial expression recognition model fine-tuned on the FER2013 dataset based on Microsoft's BEiT model

Computer VisionTransformers