C

Coco Instance Eomt Large 1280

Developed by tue-mps
This paper proposes a method to reinterpret Vision Transformer (ViT) as an image segmentation model, demonstrating ViT's potential in image segmentation tasks.
Downloads 105
Release Time : 3/26/2025

Model Overview

By redesigning the ViT architecture, this model efficiently performs image segmentation tasks, offering a new perspective on utilizing Transformer architectures for computer vision problems.

Model Features

Innovative Application of ViT Architecture
Innovatively applies the ViT architecture, originally designed for image classification, to image segmentation tasks.
Efficient Segmentation Performance
Demonstrates the efficient performance of Transformer architectures in image segmentation tasks.
Novel Perspective
Provides a new perspective on rethinking the use cases of ViT architecture.

Model Capabilities

Image Segmentation
Semantic Segmentation
Instance Segmentation

Use Cases

Computer Vision
Medical Image Analysis
Used for segmenting organs or lesion areas in medical images.
Autonomous Driving
Object segmentation in road scene understanding.
Remote Sensing Image Processing
Land Use Classification
Segmentation of different land types in satellite images.
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