Time Efficiency
Reduced interior visualization time from days to seconds, streamlining the client approval process.
Azati developed a mobile and web application for an interior design agency that allows users to instantly change room wallpapers on photos taken with their smartphones. The application leverages AI and computer vision to perform semantic segmentation and realistic visualization of wallpaper replacements.
required to generate a photorealistic wallpaper preview
accuracy of semantic segmentation
wallpaper variations instantly visualized per room photo
The client needed to eliminate long and costly 3D rendering cycles that delayed approvals and frustrated customers, while also overcoming the limitations of existing design apps that worked only with preset interiors. They wanted a fast, intuitive tool that could instantly visualize new wallpapers on any user-uploaded photo, helping clients make confident decisions and reducing the agency’s manual effort for repeated design iterations.
Clients frequently request realistic previews of interior designs, particularly with new wallpapers, but traditional 3D rendering takes several days and is expensive. Azati proposed creating a lightweight AI-based application capable of delivering realistic results in seconds using a smartphone camera, reducing time and cost while maintaining high visual quality.
Existing mobile apps only work with predefined interior images and offer very limited customization, failing to meet client expectations. Azati suggested implementing semantic segmentation and lighting-aware rendering, allowing the application to model any user-uploaded photo and apply wallpapers realistically for a fully personalized interior preview.
Detecting and separating room elements such as walls, floors, ceilings, niches, arches, and furniture is technically challenging. Azati designed AI algorithms that accurately segment all structural and decorative components to ensure correct placement of wallpapers and realistic depth perception in the final image.
Applying wallpapers convincingly requires realistic lighting and depth adjustments. Azati introduced advanced lighting and depth analysis to adapt wallpapers naturally to the room’s existing illumination, preventing artificial-looking results and ensuring photorealistic previews.
Developed a single application compatible with both smartphones and web browsers, maximizing accessibility and allowing users to visualize wallpapers anytime and anywhere.
Implemented AI-driven semantic segmentation to detect room structures, walls, floors, ceilings, and decorations accurately, forming the foundation for realistic wallpaper replacement.
Incorporated lighting and depth analysis to ensure new wallpapers blend seamlessly with existing room conditions, preserving shadows, highlights, and geometry for photorealistic results.
Designed an intuitive interface enabling users to experiment with multiple wallpaper options instantly, providing interactive previews and simplifying decision-making.
Enabled immediate application of wallpapers to user-uploaded photos, reducing visualization time from days to seconds and significantly streamlining the client approval process.
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Inquire for more infoAllows users to instantly replace wallpapers on uploaded photos without manual editing, giving immediate feedback on interior design choices.
Detects structural elements like walls, floors, ceilings, niches, arches, and furniture, ensuring that wallpapers are applied accurately and realistically.
Analyzes lighting and depth to ensure wallpapers blend naturally with existing room conditions, maintaining shadows, highlights, and perspective for a photorealistic effect.
Provides a variety of colors, textures, and patterns for wallpapers, enabling users to explore design alternatives and select the best visual fit for their space.
Reduced interior visualization time from days to seconds, streamlining the client approval process.
Enabled clients to interactively test design options and make decisions faster.
Replaced traditional 3D rendering with accessible AI-based modeling, democratizing design visualization.
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