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Ade20k Panoptic Eomt Large 1280

Developed by tue-mps
This paper proposes an image segmentation model based on Vision Transformer (ViT), revealing the potential of ViT in image segmentation tasks.
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Release Time : 3/26/2025

Model Overview

This model achieves efficient image segmentation through the Vision Transformer architecture, demonstrating the versatility of ViT in computer vision tasks.

Model Features

ViT-Based Architecture
Utilizes the Vision Transformer architecture for image segmentation, showcasing ViT's competitiveness in tasks traditionally dominated by CNNs.
Efficient Segmentation
Achieves efficient segmentation of image regions through the self-attention mechanism of Transformers.

Model Capabilities

Image Segmentation
Visual Feature Extraction

Use Cases

Computer Vision
Medical Image Segmentation
Can be used for segmenting organs or lesion areas in medical imaging.
Autonomous Driving Scene Understanding
Helps autonomous driving systems identify different objects and regions in road scenes.
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