How Looksy Virtual Try-On Technology Works

The Technology Behind Virtual Try-On

Looksy uses state-of-the-art artificial intelligence to create realistic virtual try-on experiences. Here’s how the technology works.

AI Try-On Technology

Looksy is powered by cutting-edge artificial intelligence and machine learning that transforms how customers shop for apparel online. Our AI models deliver photorealistic virtual try-on results in 15-20 seconds.

How AI Powers Virtual Try-On

Core AI Technologies:

Convolutional Neural Networks (CNNs)

Deep learning models that analyze images, detect features, and understand garment structure

Generative Adversarial Networks (GANs)

AI systems that generate realistic garment renderings adapted to each customer’s body

Computer Vision & Pose Estimation

Advanced algorithms that map body structure, detect poses, and understand spatial relationships

Style Transfer Algorithms

Machine learning techniques that maintain garment patterns, colors, and textures during rendering

AI Model Training

What makes Looksy’s AI accurate:

100+ million parameters: Sophisticated neural networks capable of understanding complex garment-body relationships
Millions of training examples: Models trained on diverse datasets of garments, body types, skin tones, and poses
Continuous learning: AI improves over time as it processes more try-ons
Apparel-specific training: Unlike generic AI, Looksy’s models are trained exclusively on fashion products

Looksy’s AI is continuously updated with new training data to improve accuracy, support more product types, and adapt to fashion trends.

AI vs. Traditional Virtual Try-On

Why AI-powered try-on is superior:

Approach	Traditional (AR Overlay)	AI-Powered (Looksy)
Realism	Basic overlay, looks fake	Photorealistic rendering
Adaptation	No body-specific fitting	Adapts to each body type
Speed	Real-time but low quality	15-20 seconds, high quality
Accuracy	60-70%	90-95%
Garment Detail	Limited	Preserves patterns, logos, textures

AI-powered virtual try-on produces realistic previews that help customers make confident purchase decisions, not just basic overlays.

High-Level Overview

1. Image Analysis

AI analyzes the product image and customer selfie

2. Body Mapping

Computer vision identifies body structure and positioning

3. Garment Adaptation

AI adapts the garment to match body shape and pose

4. Realistic Rendering

Advanced rendering creates a photorealistic composite

Total time: 15-20 seconds from upload to result

Step-by-Step Process

Step 1: Customer Uploads Selfie

What happens:

Customer clicks “Try On”
Takes photo or uploads from library
Image is sent securely to Looksy servers

Technical details:

Image is compressed for fast upload
HTTPS encryption ensures security
Original image is not stored after processing

Step 2: Face and Body Detection

What the AI does:

Identifies facial landmarks (eyes, nose, mouth)
Detects body pose and positioning
Measures proportions and dimensions
Identifies skin tone and lighting conditions

Technologies used:

Convolutional neural networks (CNNs)
Facial landmark detection algorithms
Pose estimation models
Color analysis and tone mapping

Output: Body map with key points and measurements

Step 3: Product Image Analysis

What the AI does:

Isolates the garment from background
Identifies garment type and structure
Detects patterns, colors, and textures
Maps neckline, sleeves, and hemline

Technologies used:

Semantic segmentation
Object detection
Texture analysis
Edge detection

Output: Garment mask and feature map

Step 4: Garment Adaptation

What the AI does:

Adapts garment to match body shape
Adjusts proportions for realistic fit
Maintains garment characteristics (patterns, logos)
Applies perspective and depth

Technologies used:

Generative adversarial networks (GANs)
Style transfer algorithms
3D pose estimation
Geometric transformations

Output: Adapted garment ready for compositing

Step 5: Realistic Rendering

What the AI does:

Blends garment with selfie
Matches lighting conditions
Applies shadows and highlights
Ensures natural edges and transitions

Technologies used:

Image synthesis
Lighting estimation
Shadow rendering
Color matching

Output: Final photorealistic try-on result

The entire pipeline processes in 15-20 seconds on Looksy’s servers, with no strain on your store or customer devices.

AI Models and Training

Deep Learning Architecture

Model types:

Encoder-decoder networks: For image segmentation
GANs (Generative Adversarial Networks): For realistic garment rendering
CNNs (Convolutional Neural Networks): For feature detection
Transformer models: For attention mechanisms

Model size: 100+ million parameters Training data:

Millions of garment images
Diverse body types and skin tones
Various lighting conditions
Multiple garment categories

Looksy’s models are continuously updated with new data to improve accuracy and support more product types.

What Makes Looksy’s AI Different

Advantages over competitors:

Apparel-specific training: Models trained exclusively on clothing (not generalized)
Diverse datasets: Inclusive training data across body types and skin tones
Shopify-optimized: Fine-tuned for e-commerce product images
Fast inference: Optimized for 15-20 second rendering
Continuous learning: Models improve over time with usage

Technical Infrastructure

Server Architecture

Where processing happens:

All AI processing occurs on Looksy’s cloud servers
Not on your Shopify store
Not on customer devices

Benefits:

No performance impact on your store
Consistent experience across devices
Access to powerful GPU servers
Regular model updates without customer action

Cloud Infrastructure

Stack:

GPU-accelerated servers for AI inference
Content delivery network (CDN) for fast global access
Auto-scaling to handle traffic spikes
Multi-region deployment for low latency

Uptime: 99.9% SLA (Pro plan)

Data Flow

Customer device → Looksy API (HTTPS)
Looksy API → AI processing servers (internal)
AI servers → Result generation
Result → Customer device (HTTPS)
Image deleted (not stored)

Privacy: Customer photos are processed and immediately discarded. Not stored.

Performance Optimization

Speed Optimizations

How we achieve 15-20 second rendering:

Model quantization: Reduced model size without accuracy loss
Batch processing: Efficient GPU utilization
Caching: Product images cached after first use
Edge computing: Processing near user for low latency
Asynchronous operations: Parallel processing where possible

Accuracy vs. Speed Trade-Offs

Our approach:

Prioritize speed without sacrificing quality
95%+ accuracy maintained
Real-time rendering over perfect detail
Good enough to help purchase decisions

If perfect photorealism were required, rendering would take 30+ seconds. Looksy balances accuracy and speed for optimal e-commerce experience.

Handling Edge Cases

Challenging Scenarios

Low-Quality Selfies

Challenge: Dark, blurry, or angled selfiesHow we handle it:

Image enhancement algorithms
Brightness and contrast adjustment
Noise reduction
Pose correction (to extent possible)

Limitation: Very poor selfies may still produce suboptimal results

Complex Garments

Challenge: Heavy textures, sheerness, embellishmentsHow we handle it:

Texture approximation
Pattern preservation
Structural understanding

Limitation: Fine details may be simplified

Unusual Poses

Challenge: Profile views, angled selfiesHow we handle it:

3D pose estimation
Perspective adjustment
Best-effort garment placement

Note: Works with any angle - the AI adapts to different poses

Poor Product Images

Challenge: Busy backgrounds, bad lighting, low resolutionHow we handle it:

Background removal algorithms
Garment isolation
Edge refinement

Limitation: Cannot fix fundamentally poor images

Privacy and Security

Data Handling

Customer images:

Processed in memory only
Never stored to disk
Deleted immediately after rendering
No usage for training (without explicit consent)

Product images:

Cached temporarily for performance
Public images (already on your store)
Standard retention policies

Compliance:

GDPR compliant
CCPA compliant
SOC 2 Type II certified (Pro plan)

Encryption

In transit:

TLS 1.3 encryption
HTTPS for all communications
Secure API endpoints

At rest:

No customer data stored
Product images encrypted
Database encryption

Looksy is privacy-first. Customer photos are never stored, shared, or used for training without explicit consent.

Future Technology Roadmap

Upcoming Enhancements

Coming Soon:

Multi-item try-on (outfit combinations)
Enhanced fabric texture rendering
AR try-on (live camera mode)
3D garment rotation
Custom fit recommendations
Virtual fitting room (full outfit try-on)
Social try-on features

Roadmap subject to change based on technical feasibility and merchant feedback.

Technical Specifications

API Specifications

Request format:

POST /api/v1/try-on
Content-Type: multipart/form-data

{
  "product_id": "12345",
  "selfie": <image_file>,
  "options": {
    "quality": "high",
    "fast_mode": false
  }
}

Response format:

{
  "success": true,
  "result_url": "https://cdn.looksy.ai/results/abc123.jpg",
  "processing_time_ms": 3421,
  "confidence_score": 0.94
}

Rate limits:

Standard: 100 requests/minute
Pro: 1,000 requests/minute

Supported Formats

Input images:

JPEG, PNG
Minimum resolution: 800px
Maximum file size: 5MB
Color space: RGB

Output images:

JPEG (optimized for web)
Resolution: matches input (max 2048px)
Compression: 85% quality

For Developers

Webhooks

Available events:

try_on.started
try_on.completed
try_on.failed

Webhook payload:

{
  "event": "try_on.completed",
  "timestamp": "2026-01-23T10:30:00Z",
  "data": {
    "try_on_id": "abc123",
    "product_id": "12345",
    "result_url": "https://cdn.looksy.ai/results/abc123.jpg",
    "processing_time_ms": 3421
  }
}

Custom Integrations

Pro plan features:

API access for custom implementations
Webhook integrations
White-label rendering
Custom branding

Contact sales@looksy.ai for details.

Common Technical Questions

Does processing happen on my server?

No. All AI processing happens on Looksy’s cloud servers. Your store only handles displaying the button and result.

What if Looksy's servers are down?

Button gracefully degrades. If servers are unreachable, button won’t appear or will show “Try-on temporarily unavailable.” Your store continues working normally.

Can I use Looksy offline?

No. Virtual try-on requires internet connection for processing. The AI runs on cloud servers, not locally.

How do you handle traffic spikes?

Auto-scaling infrastructure handles surges automatically. Tested up to 10,000 simultaneous try-ons. No manual intervention needed.

Next Steps

Limitations

Understand what virtual try-on can and cannot do

What Makes Looksy Different

See how Looksy compares to competitors

Installation Guide

Get started in 10 minutes

Image Requirements

Optimize for best AI performance

Getting Started

Product Setup

Integration & Customization

Analytics & ROI

Use Cases & Benefits

Troubleshooting & FAQs

About Looksy

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Solutions & Guides

​The Technology Behind Virtual Try-On

​AI Try-On Technology

​How AI Powers Virtual Try-On

Convolutional Neural Networks (CNNs)

Generative Adversarial Networks (GANs)

Computer Vision & Pose Estimation

Style Transfer Algorithms

​AI Model Training

​AI vs. Traditional Virtual Try-On

​High-Level Overview

1. Image Analysis

2. Body Mapping

3. Garment Adaptation

4. Realistic Rendering

​Step-by-Step Process

​Step 1: Customer Uploads Selfie

​Step 2: Face and Body Detection

​Step 3: Product Image Analysis

​Step 4: Garment Adaptation

​Step 5: Realistic Rendering

​AI Models and Training

​Deep Learning Architecture

​What Makes Looksy’s AI Different

​Technical Infrastructure

​Server Architecture

​Cloud Infrastructure

​Data Flow

​Performance Optimization

​Speed Optimizations

​Accuracy vs. Speed Trade-Offs

​Handling Edge Cases

​Challenging Scenarios

​Privacy and Security

​Data Handling

​Encryption

​Future Technology Roadmap

​Upcoming Enhancements

​Technical Specifications

​API Specifications

​Supported Formats

​For Developers

​Webhooks

​Custom Integrations

​Common Technical Questions

​Next Steps

Limitations

What Makes Looksy Different

Installation Guide

Image Requirements

The Technology Behind Virtual Try-On

AI Try-On Technology

How AI Powers Virtual Try-On

AI Model Training

AI vs. Traditional Virtual Try-On

High-Level Overview

Step-by-Step Process

Step 1: Customer Uploads Selfie

Step 2: Face and Body Detection

Step 3: Product Image Analysis

Step 4: Garment Adaptation

Step 5: Realistic Rendering

AI Models and Training

Deep Learning Architecture

What Makes Looksy’s AI Different

Technical Infrastructure

Server Architecture

Cloud Infrastructure

Data Flow

Performance Optimization

Speed Optimizations

Accuracy vs. Speed Trade-Offs

Handling Edge Cases

Challenging Scenarios

Privacy and Security

Data Handling

Encryption

Future Technology Roadmap

Upcoming Enhancements

Technical Specifications

API Specifications

Supported Formats

For Developers

Webhooks

Custom Integrations

Common Technical Questions

Next Steps