# Large-scale image processing

A vision Transformer (ViT)-based image feature model, pre-trained on the LVD-142M dataset using the self-supervised DINOv2 method.

AIM-v2 is an image feature extraction model based on the timm library, designed with large patches for high-resolution image processing.

AIM-v2 is an image encoder model based on the timm library, suitable for image feature extraction tasks.

An improved direct segmentation any model based on the Segformer architecture, designed for boundary detection and image segmentation tasks

A Vision Transformer (ViT) image feature model with registers, pre-trained using self-supervised DINOv2 method on the LVD-142M dataset.

A visual transformer (ViT) image feature model with registers, pre-trained using the self-supervised DINOv2 method on the LVD-142M dataset.

A self-supervised image feature model based on Vision Transformer (ViT), pre-trained using the DINOv2 method on the LVD-142M dataset, suitable for image classification and feature extraction tasks.

A giant vision Transformer (ViT)-based image feature extraction model, pre-trained using self-supervised DINOv2 method on the LVD-142M dataset

A Vision Transformer (ViT)-based image feature model, pre-trained using self-supervised DINOv2 method on the LVD-142M dataset

RegNet model trained on imagenet-1k, pre-trained in a self-supervised manner on billions of random web images before fine-tuning