
The Meme as Masterpiece: Seedance 2.5 vs Kling O3 vs Wan 3.0
Why we should judge AI video models the way we judge Donatello and Michelangelo.
7 min read
ReadHow AI is changing fashion imagery, from virtual try-on and AI models to the research behind them.
44 articles in this category

Why we should judge AI video models the way we judge Donatello and Michelangelo.
7 min read
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I photographed one jacket 12 different ways and ran every set through the FASHN Agent. Here is what worked: views, fit, light and details.
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How From the Future integrated FASHN's virtual try-on API into two interactive FIFA and KIA Canada fan activations.
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Learn how to create the ghost mannequin effect for your product photos, from the full studio process with a mannequin and Photoshop to the AI way that turns one phone photo into a finished packshot.
11 min read
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The new FASHN skill helps Claude Code, Codex, Cursor, and other coding agents integrate FASHN into real projects with less documentation handoff. Learn how to install it, use it for project integration, and review the secure server-side pieces it adds.
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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.
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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.
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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.
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We're open-sourcing FASHN VTON v1.5, a segmentation-free virtual try-on model that generates photorealistic results directly in pixel space.
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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.
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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.
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Turn plain product photos into festive, on-brand holiday visuals with FASHN AI. From cozy family scenes to matching Christmas sweaters, you can create warm, professional campaign imagery in minutes.
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