Computer Vision Experiment

AI Virtual Try-On

A sophisticated image-to-image synthesis pipeline that allows users to virtually try on clothing using Diffusion models and human parsing.

Timeline2024
LocationProprietary

The Challenge

Preserving garment texture and patterns while naturally draping them over diverse human body poses.

Pain Points

  • • Texture blurring in early models
  • • Pose misalignment
  • • Inconsistent fabric patterns

The Solution

A two-stage warping module followed by a refinement Diffusion pass ensuring texture consistency and pose preservation using ControlNet.

Impact

  • • High-fidelity texture preservation
  • • Support for complex human poses
  • • Scalable e-commerce integration

Technical Depth

Two-Stage Warping

Uses a dedicated warping module followed by a refinement Diffusion pass to ensure garments naturally drape over diverse body poses.

Texture Preservation

Maintains intricate fabric details and patterns from the original clothing image while adapting to human body geometry.

Pose Preservation

Leverages ControlNet to ensure the user's pose remains identical after garment synthesis.

Technology Stack

frontend

ReactCanvas API

backend

FastAPIPyTorch

intelligence

Stable DiffusionControlNetHuman Parsing

infra

GPU Cloud