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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 de abril de 2026

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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 de janeiro de 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 de janeiro de 2026

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Upcoming App Updates: Collaboration, Parallel Tools, and a Smarter Credits System

A faster, more collaborative FASHN app is coming, with team workspaces, multiple outputs, parallel tool runs, and a new credit system that boosts flexibility while keeping plan pricing the same.

FASHN Team14 de novembro de 2025

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AI Fashion News 2025: How Brands Are Using AI in Campaigns

AI is becoming mainstream in fashion, powering campaigns and catalogs as disclosure and ethics questions grow. Major brands already use it; see how it’s done.

Brenda Barron1 de outubro de 2025

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