META FIT GenAI: Virtual Try-On with Generative AI
Migrating a virtual try-on system from PASTA-GAN++ to Gemini and Vertex AI — replacing an entire GPU pipeline with API calls and resolving the body diversity problem that GANs could never solve.
3 articles
Part 1: From GANs to Generative AI — Why and How the Migration Happened
Google proved that generative AI can do virtual try-on. Could the same approach replace our entire GAN pipeline? This is the story of migrating from PASTA-GAN++ to Gemini and Vertex AI — simplifying a multi-stage GPU pipeline into a single API call.
Part 2: Nano Banana Virtual Try-On — 16 Test Cases and What They Revealed
Systematic testing of Gemini's image generation for virtual try-on across three phases: noisy inputs, clean images, and high-resolution action poses. The key finding: resolution matters more than any preprocessing pipeline.
Part 3: The 3-Engine Showdown — PASTA-GAN++ vs Nano Banana vs Vertex AI VTO
A head-to-head comparison of three generations of virtual try-on technology across 12 test cases. The results reveal not just incremental improvement, but a generational leap — especially in body diversity, where GANs fundamentally failed.