This Weathered Dirty Wall texture is a meticulously crafted seamless 3D representation inspired by the stone wall 02 type showcasing the authentic characteristics of a man-made rock surface. The base substrate consists of mineral-rich stone with a coarse grain orientation reflecting natural geological formations shaped by time and environmental exposure. Embedded within the porous matrix are binders and organic residues that have accumulated over years lending an aged rough and weathered appearance. The wall’s dominant brown hue emerges from earthy pigments and oxide layers that have settled unevenly across the surface creating a matte finish punctuated by chipped cracked and damaged areas. These imperfections reveal the wall’s vulnerability to natural weathering and wear while dirt and grime lodged in crevices enhance the texture’s overall dirty and rough character perfectly capturing the essence of an old man-made stone wall.
Designed for physically based rendering workflows this PBR texture includes a comprehensive set of maps optimized for realistic shading and surface detail. The Albedo (BaseColor) map presents natural brown tones interspersed with dirt patches delivering true-to-life diffuse coloration. The Normal map intricately encodes fine cracks chipped edges and the coarse grain structure of the rock substrate adding convincing tactile depth. Roughness maps emphasize the matte weathered quality of the surface controlling light diffusion to highlight the gritty aged nature of the wall while the Metallic channel remains minimal accurately reflecting the non-metallic stone base. Ambient Occlusion enhances shadow depth in recessed areas and Height/Displacement maps provide elevation data for simulating surface irregularities such as chips and cracks through parallax or tessellation effects. All these maps are tileable and come in both PNG and EXR formats ensuring seamless integration across Blender Unreal Engine and Unity pipelines.
Available in high-resolution 4K with an optional upgrade to 8K this texture strikes a balance between rich detail and efficient performance making it ideal for architectural visualization game environments and any 3D scenes requiring an authentic physically based weathered dirty wall surface. For optimal results it is recommended to adjust the UV scale to match your specific wall dimensions maintaining natural detail density and avoiding visible repetition. Additionally fine-tuning roughness values allows subtle control over the interplay of dirt accumulation and stone reflectivity enhancing realism under various lighting conditions. This robust free-download-ready texture set supports the metal/rough PBR workflow providing versatile and realistic material solutions for diverse digital content creation needs.
Using This PBR Texture in Blender
Import the texture maps into Blender with sRGB color space for albedo/base color and
Non-Color for normal, roughness, metallic, AO, height, and ORM maps. Connect normal maps
through a Normal Map node, then adjust UV scale with a Mapping node so the material repeats naturally on
your model.
- Albedo -> Principled BSDF Base Color
- Roughness -> Roughness, Metallic -> Metallic
- Normal -> Normal Map node -> Normal
- Height -> Bump or Displacement depending on render setup
For the full step-by-step setup, see
How to Use Seamless Textures in Blender.
Browse related material examples in
wood,
concrete, and
metal.
FAQ
Is this texture seamless and tileable?
Yes. This texture is designed as a seamless tileable PBR material, so it can repeat across large surfaces without visible borders.
Which resolutions and formats are available?
You can download PNG/WEBP versions and use 1K, 2K, 4K and 8K download options when available on the page.
Can I use it in Blender, Unreal Engine and Unity?
Yes. The download options and engine-mapped ZIP workflow are designed for Blender, Unreal Engine, Unity Standard, URP and HDRP material pipelines.
Is commercial use allowed?
Yes. The texture is available under the AITextured free commercial license. Review the license page for redistribution and AI-training restrictions.
