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Google Research and UW's FIT: What It Means for Virtual Try-On

FIT from Google Research and the University of Washington is the first large-scale fit-aware virtual try-on dataset with ground-truth body and garment measurements. We look at what is new, what is still missing, and what it could mean for virtual try-on experiences going forward.

Dan Bochman17 Nisan 2026

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How to Add Virtual Try-On to Your Store Like Zara

Zara added virtual try-on to their app, and the reviews are positive. Here's why it matters for every fashion store, and how you can add the same feature to yours using the FASHN API.

Aya Bochman15 Nisan 2026

Oku

Fashion AI: 7 Key Use Cases in 2026

Fashion AI is reshaping the industry from design to delivery. Explore 7 key use cases, from virtual try-on and AI photography to smart personalization, driving fashion forward in 2026.

Brenda Barron23 Şubat 2026

Oku

Open-Sourcing FASHN VTON v1.5: Maskless Virtual Try-On in Pixel Space

We're open-sourcing FASHN VTON v1.5, a segmentation-free virtual try-on model that generates photorealistic results directly in pixel space.

FASHN Team27 Ocak 2026

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Open-Sourcing FASHN Human Parser: Production-Grade Semantic Segmentation for Fashion

We're releasing a state-of-the-art human parsing model to the open-source community. A SegFormer-B4 fine-tuned for fashion applications, available via PyPI, HuggingFace, and GitHub. This is the first step in open-sourcing our virtual try-on stack.

FASHN Team11 Ocak 2026

Oku

How to Create Consistent On-Model Product Images with AI

Learn two proven methods to create consistent AI models for on-model product images. Use Try On to re-dress existing models or Face Reference to generate new poses while maintaining the same model identity across all your visuals.

Brenda Barron30 Aralık 2025

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