8 articles tagged with "Computer Vision"
Series 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.
Series 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.
Series 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.
Series The origin story of META FIT: how a decades-old vision of seeing yourself in clothes before buying evolved from hardware kiosks to GAN-powered virtual try-on, plus a comprehensive survey of 15+ VTON research models.
Series A code-level walkthrough of the Parser-Free Appearance Flow Network: Feature Pyramid encoding, CUDA-accelerated correlation kernels, optical flow warping, and the ResUnet generator that composites garments onto people.
Series A deep dive into Generative Adversarial Networks: how the generator-discriminator dynamic works, why GANs dominated image generation before diffusion models, and how they power virtual try-on systems.
Series How OpenPose skeletal detection, Graphonomy human parsing, and custom body measurement algorithms work together to enable accurate virtual fitting — plus an exploration of PiFu for 2D-to-3D reconstruction.
Series What the GAN-based virtual try-on system achieved, where it failed (and why), the smartphone app design, and how diffusion models are changing everything for the next generation of META FIT.