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Ade20k Semantic Eomt Large 512
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Ade20k Semantic Eomt Large 512

Developed by tue-mps
This model is developed based on the paper 'Your ViT is Actually an Image Segmentation Model' and is a Vision Transformer model for image segmentation tasks.
Image Segmentation
PyTorch
Open Source License:MIT#ViT Image Segmentation#Vision Transformer#High-Precision Segmentation
Downloads 108
Release Time : 3/26/2025

Model Overview

This model explores the application of Vision Transformers (ViT) in image segmentation tasks, demonstrating the potential of the ViT architecture in pixel-level prediction tasks.

Model Features

Transformer-Based Image Segmentation
Applies the Vision Transformer architecture to image segmentation tasks, exploring ViT's performance in pixel-level prediction.
Efficient Segmentation Capability
Utilizes the self-attention mechanism of Transformers to capture long-range dependencies, improving segmentation accuracy.

Model Capabilities

Image Segmentation
Pixel-Level Prediction
Semantic Segmentation

Use Cases

Computer Vision
Medical Image Segmentation
Used for segmenting organs or lesion areas in medical imaging.
Autonomous Driving Scene Understanding
Used for object segmentation and recognition in road scenes.
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