# Urban Scene Segmentation

A semantic segmentation model based on the Segformer architecture, optimized for the Cityscapes dataset

A lightweight semantic segmentation model based on Segformer architecture, pre-trained on the Cityscapes dataset

A semantic segmentation model based on the Segformer architecture, specifically optimized for the Cityscapes dataset

A lightweight semantic segmentation model based on the Segformer architecture, pre-trained on the Cityscapes dataset

SegFormer is a semantic segmentation model based on Transformer architecture, fine-tuned on the CityScapes dataset, suitable for image segmentation tasks at 1024x1024 resolution.

SegFormer is a Transformer-based semantic segmentation model fine-tuned on the Cityscapes dataset, suitable for image segmentation tasks at 1024x1024 resolution.

SegFormer is a Transformer-based semantic segmentation model fine-tuned on the CityScapes dataset, suitable for semantic segmentation tasks in urban scene images.

SegFormer is a Transformer-based semantic segmentation model fine-tuned on the Cityscapes dataset, suitable for road scene segmentation tasks.

This SegFormer model is fine-tuned on the CityScapes dataset at 1024x1024 resolution, featuring a hierarchical Transformer encoder and lightweight all-MLP decoder head architecture.