Catches is a groundbreaking startup that's turning the world of online fashion shopping upside down. As Lead Developer, I'm at the forefront of creating an innovative platform that combines cutting-edge 3D technology with the convenience of online shopping.
Fashion Like Never Before:
- Personalized Avatars: Custom 3D characters tailored to your unique body proportions
- Virtual Try-On: See how garments look and fit on your personal avatar before buying
- High-Fidelity Rendering: Photorealistic clothing and avatar quality via Unreal Engine
- Accurate Sizing: No more guessing sizes or settling for "one-size-fits-all"
- Accessible Anywhere: Browser-based experience powered by Pixel Streaming
Say goodbye to guessing your size or settling for "one-size-fits-all." At Catches, we create a personalized avatar just for you, tailored to your unique proportions. Thanks to Unreal Engine's character customizer that we created, it's like having a virtual tailor at your fingertips.
Technical Implementation:
- Custom Unreal Engine character customization system
- Parametric body modeling with accurate proportions
- Dynamic clothing simulation and physics
- Pixel Streaming for web-based 3D visualization
- AWS infrastructure for scalable garment delivery
- Automated asset pipeline for fashion catalog management
Ever wanted to try on high-end fashion from the comfort of your own home? With Catches, I harnessed the power of Pixel Streaming to bring you stunningly detailed garments and avatars, no matter where you are. It's like having a fashion show in your living room.
Character Customization System:
- Body Measurements: Input height, weight, and key body measurements
- Proportional Accuracy: Avatar scaled to match real-world proportions
- Realistic Physics: Clothing drapes and fits naturally on custom body types
- Multiple Views: 360-degree rotation and zoom for detailed inspection
- Style Preferences: Customizable avatar appearance and features
Behind the scenes, I've harnessed the might of AWS to automate garment downloads seamlessly. Our pipeline automatically processes new fashion items, converts them to optimized 3D assets, and integrates them into the platform without manual intervention.
AWS Automation Pipeline:
- S3 bucket storage for 3D garment assets
- Lambda functions for automated asset processing
- CloudFront CDN for fast global content delivery
- EC2 auto-scaling for Pixel Streaming servers
- DynamoDB for catalog and user data management
- EventBridge for orchestrating the asset pipeline
Key Innovations:
- Zero Downloads: Entire experience runs in web browser via Pixel Streaming
- True-to-Life Fit: Accurate representation of how clothes will look on your body
- Reduced Returns: Customers know exactly what they're buying
- Premium Quality: High-end fashion rendered with photorealistic detail
- Instant Gratification: Try on entire collections in minutes
The platform addresses one of the biggest challenges in online fashion retail: the uncertainty of fit and appearance. By providing an accurate, personalized virtual try-on experience, we're reducing return rates and increasing customer satisfaction.
Technology Stack:
- Unreal Engine 5 for 3D rendering and character systems
- Custom character customization and measurement system
- Pixel Streaming for browser-based high-quality 3D
- AWS cloud infrastructure (S3, Lambda, EC2, CloudFront)
- Automated 3D asset processing pipeline
- Responsive web interface with real-time 3D interaction
Impact on Fashion E-Commerce:
- Solving the online sizing problem with personalized avatars
- Reducing returns and environmental waste
- Making high-end fashion more accessible
- Enabling confident purchasing decisions
- Creating engaging, interactive shopping experiences
Catches stands as a sophisticated solution to the 'virtual try-on' challenge, pushing the boundaries of what deterministic physics and Pixel Streaming could achieve at the time. While we successfully built a pipeline for high-fidelity, accurate simulations, the rapid emergence of Generative AI has since shifted the paradigm.
Today, the industry is evolving from heavy, real-time rendering toward lightweight, probabilistic AI inference. Looking back, this project represents a masterclass in cloud automation and physics-based engineering—a necessary bridge in the evolution of fashion tech—even as the definition of 'virtual try-on' continues to be redefined by algorithmic advances.