C

Coco Panoptic Eomt Large 1280

Developed by tue-mps
This paper proposes a novel perspective by treating Vision Transformer (ViT) as an image segmentation model and explores its potential in image segmentation tasks.
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Release Time : 3/26/2025

Model Overview

By reinterpreting the architecture of Vision Transformer (ViT), this model demonstrates its effectiveness in image segmentation tasks. The paper investigates ViT's performance in segmentation and may propose improvements.

Model Features

ViT as a Segmentation Model
Reinterprets the Vision Transformer (ViT) architecture to make it suitable for image segmentation tasks.
Efficient Segmentation
Utilizes ViT's attention mechanism to achieve efficient image segmentation.
Cross-Domain Applications
Potentially applicable to various image segmentation scenarios, such as medical imaging and autonomous driving.

Model Capabilities

Image Segmentation
Attention Mechanism Analysis
High-Resolution Image Processing

Use Cases

Medical Imaging
Organ Segmentation
Used for organ segmentation tasks in medical imaging.
Autonomous Driving
Road Scene Segmentation
Used for road and obstacle segmentation in autonomous driving.
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