Doppl
Doppl is an early experimental app from Google Labs that lets users try on any look and explore their style by uploading a full-body photo or selecting an AI model. It supports virtual try-on of tops, bottoms, and dresses from images saved from social media or camera-roll screenshots, and adds video animations to bring looks to life. It guides users through setup, recommends photo-quality guidelines for accurate styling, such as high-resolution, full-body, form-fitting photos in bright, even lighting, and offers tips for optimal outfit images. Generated outputs include invisible digital watermarks and may contain errors in fit, body shape, or garment details; they do not indicate size availability or fit suggestions. Users can download or share static or animated looks, manage and delete items in the Looks gallery, and provide feedback via the in-app menu. When an outfit image is incomplete or unsupported, Doppl will imagine missing elements or revert to a default basic look.
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Zeekit
Zeekit offers a new and more interactive shopping experience for fashion brands. Our patented technology is used to dress anyone virtually in any item of clothing found online. Founded by Yael Vizel, Nir Appleboim and Alon Kristal. Combining fashion and technology, Zeekit has developed the first dynamic virtual fitting room, giving every person the chance to see themselves in any item of clothing found online. Based on real-time image processing technology, Zeekit uses its patented technology to map a person's image into thousands of segments. Clothing is processed in a similar manner and the equivalent points of the two are re-mapped into one final simulation, showing a person fully dressed while taking into account body dimensions, fit, and the fabric of the garment.
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CamClo3D
CamClo3D is an AI-powered virtual try-on and apparel visualization platform designed for fashion brands, eCommerce sellers, and apparel manufacturers. It allows users to transform basic garment images into high-quality, model-worn product visuals without traditional photoshoots.
The platform uses advanced AI to map clothing onto realistic human models while preserving accurate fabric texture, fit, folds, shadows, and garment structure. Users can upload flat-lay images, mannequin shots, or product photos and generate studio-quality on-model images within minutes.
CamClo3D also enables background customization, model selection, pose variation, and fast visual iteration for catalog creation, ads, and marketplaces. It reduces photoshoot costs, shortens production time, and helps brands scale product listings efficiently. The solution is especially useful for D2C brands, marketplaces, and apparel startups seeking consistent, high-converting product imagery at scale.
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Tryona
Tryona is an AI-powered virtual try-on platform that helps fashion brands and online stores bring their collections to life. With Tryona, shoppers can instantly see how clothes look on a person — whether on themselves or on a realistic model — before they buy.
Using advanced image processing and generative AI, Tryona transforms garment clothing photos into realistic try-on previews. Customers simply upload a selfie or use a preset model, choose an outfit, and see a lifelike image of the item being worn — all in seconds.
Key features include:
- Virtual Try-On: Upload or select a model and visualize how any outfit fits in a realistic way.
- Seamless Integration: Easily embed Tryona into your website, mobile app, or online store with a few lines of code or API.
- AI-Driven Fit Visualization: Smart garment alignment and lighting adjustments for photo-realistic results.
- Flexible for Brands and Developers: From startups to enterprise retailers, Tryona scales with you
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