3D Model Description: Classic and Vintage Wooden Fence Set (Lowpoly with PBR Textures)
This model set features 10 pieces of classic and vintage wooden fences, designed in lowpoly style for efficient use in games or visualization projects. Each fence model combines traditional aesthetics with vintage elements, evoking a sense of nostalgia and natural beauty. These wooden fences are crafted with lowpoly techniques, ensuring optimal performance in real-time applications such as games or AR/VR projects.
Key Features:
Classic and Vintage Design: The wooden fence design features natural wood textures, highlighting the classic and vintage style. The shapes and sizes of the fences vary, offering a range of attractive options for creative projects.
PBR Textures: Each fence is equipped with PBR (Physically-Based Rendering) textures, including realistic details like cracks, stains, and weathered wood, creating a dynamic visual quality that adapts to lighting conditions and environmental changes.
Lowpoly: The model is designed with low polygon count, making it ideal for game applications or interactive uses where performance is critical. The models maintain enough detail for a realistic appearance while being optimized for better performance.
Compatibility and Flexibility: This model set is compatible with various 3D software such as Blender, Maya, or Unity. Each fence model is designed to be used individually or combined to create longer, varied fence designs.
Number of Models: The package includes 10 variations of classic and vintage wooden fence models, allowing for versatile design options in your projects.
Technical Specifications:
- File Formats: .fbx, .obj, .blend (includes PBR texture files)
- Polygon Count: 500 to 1000 polygons per fence model (depending on variation)
- Textures: Diffuse, Normal, Roughness, Specular, and Ambient Occlusion
- Scale: Realistic scale with adjustable fence dimensions
With this package, you can add beautiful vintage wooden fence elements to your 3D world, combining high visual quality with optimized performance.