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Segformer Finetuned Segments Cmp Facade

Developed by Xpitfire
A building facade semantic segmentation model based on SegFormer architecture, capable of recognizing 12 types of architectural elements
Downloads 379
Release Time : 1/8/2023

Model Overview

This model employs a hierarchical Transformer encoder and a lightweight MLP decoder, specifically designed for pixel-level classification tasks of building front views. It can identify 12 types of architectural elements including facades, windows, doors, etc.

Model Features

Hierarchical Transformer Encoding
Position-encoding-free hierarchical feature extraction that effectively captures multi-scale architectural features
Lightweight MLP Decoder
Simplifies traditional complex decoder structures while maintaining high performance and reducing computational costs
Multi-element Recognition
Simultaneously identifies 12 types of architectural elements (facades, cornices, windows, etc.) and their spatial relationships

Model Capabilities

Building facade semantic segmentation
Pixel-level classification
Multi-scale feature extraction
Street view image analysis

Use Cases

Architectural Digitization
Historic Building Preservation
Automatically labels facade elements to assist restoration design
Accurately identifies decorative components and other detailed features
Urban Planning
Batch analysis of street architectural style composition
Statistical distribution of architectural elements across different areas
3D Reconstruction
Building Reverse Modeling
Generates preliminary 3D structures based on single front views
Provides accurate facade element segmentation masks
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