AIbase
EN
Home
Cityscapes Semantic Eomt Large 1024
C

Cityscapes Semantic Eomt Large 1024

Developed by tue-mps
This model reveals the potential of Vision Transformer (ViT) in image segmentation tasks by transforming ViT into an efficient image segmentation model through specific methods.
Image Segmentation
PyTorch
Open Source License:MIT#ViT Image Segmentation#Vision Transformer#High-Precision Segmentation
Downloads 85
Release Time : 3/26/2025

Model Overview

Based on the method proposed in the paper 'Your ViT is Actually an Image Segmentation Model,' this model demonstrates how to effectively apply the Vision Transformer architecture to image segmentation tasks, expanding the application scope of ViT.

Model Features

Innovative Application of ViT Architecture
Innovatively applies the Vision Transformer architecture to image segmentation tasks, breaking the monopoly of traditional CNNs in the segmentation field.
Efficient Segmentation Performance
Transforms the ViT model through specific methods, enabling it to maintain its original advantages while excelling in image segmentation.

Model Capabilities

Image Segmentation
Semantic Understanding
Pixel-Level Classification

Use Cases

Medical Image Analysis
Organ Segmentation
Used for precise segmentation of organs in medical CT/MRI images
Helps doctors make more accurate diagnoses and treatment plans
Autonomous Driving
Road Scene Understanding
Used for semantic segmentation of road scenes by autonomous vehicles
Enhances the autonomous driving system's understanding of complex environments
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
English简体中文繁體中文にほんご
© 2025AIbase