Accelerating Product Visualization with a Hybrid 3D × GenAI Workflow
Under Armour’s AI-enhanced Content Production
Accelerating Product Visualization with a Hybrid 3D × GenAI Workflow
Background
The Growing Need for Scalable Content
Across industries, brands face growing pressure to deliver more product visuals than ever — for launches, campaigns, social media, and e-commerce. The demand for fresh, channel-specific content never stops.
Yet most production still depends on traditional, manual workflows that are slow, costly, and hard to scale — making it difficult for brands to keep their channels supplied with updated product content.
Approach
Combining 3D Accuracy with AI Creativity
Under Armour needed both: creative control over how products are presented, and an automated workflow to create visuals at scale.
To achieve this, we built a hybrid system that combines precise 3D product data with AI-generated environments. Each visual pairs a 100% accurate digital twin with a realistic, context-rich background created by generative AI.
Technology & Workflow
From 3D Scan to AI Scene
Each product is 3D-scanned, processed, and textured to create an accurate digital twin.
Teams then adjust the scene directly in the web editor — refining lighting, angles, and brand tone — before a Generative AI workflow builds the surrounding environment through text prompts or interactive controls.
The result: coherent, photorealistic visuals that merge 3D precision with AI creativity.
Benefits
Automated Content for Any Purpose
For Under Armour China, the hybrid 3D + AI approach turned a manual, fragmented process into a scalable production model — faster to execute, easier to adapt, and far more cost-efficient.
Speed: Visuals ready in minutes instead of days.
Accuracy: 100% true-to-product representation.
Cost Efficiency: No photoshoots, no expensive CGI.
Reusability: One digital product, endless applications — from images to videos and 3D experiences.
Long Term Value
A Scalable System That Grows With the Brand
Integrated into the marketing pipeline, the system keeps generating value beyond individual campaigns.
As teams and AI models are trained, efficiency, quality, and speed improve continuously — building reusable assets, scalable workflows, and shared know-how across units and markets.
Over time, it evolves into a self-learning content ecosystem that reduces cost, increases flexibility, and strengthens brand consistency.
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