# Virtual Try-On

The AI Nail Design Lab uses artificial intelligence technology to generate unique nail art designs, quickly and accurately matching user preferences and hand features. It provides professional designs that predict trends, reducing communication costs and ensuring perfect nail art results.

FitDiT aims to address issues of low fidelity and robustness in image-based virtual try-ons. By introducing a clothing texture extractor and employing frequency domain learning alongside an expanded relaxed mask strategy, it significantly enhances the fit and detail representation of virtual try-ons. Its main advantages include the ability to generate realistic and detail-rich clothing images, applicable in various scenarios with high practical value and competitiveness. Specific pricing and market positioning have not been clearly established yet.

BooW-VTON is a research project focused on improving outdoor virtual try-on effects through mask-free pseudo data training, which enhances virtual try-on technology. Its significance lies in improving the realism and accuracy of clothing try-ons in natural environments, making it highly relevant for fashion e-commerce and virtual reality domains. According to product background information, this project is based on deep learning image generation models designed to address the unnatural integration of clothing and human bodies in traditional virtual try-ons. The project is currently free and open-source, situated in the research and development stage.

TryOffDiff is a high-fidelity garment reconstruction technology that generates standardized garment images from a single photo of an individual wearing clothing. Unlike traditional virtual try-ons, this technology aims to extract normative garment images, which poses unique challenges in capturing garment shape, texture, and complex patterns. TryOffDiff ensures high fidelity and detail retention by utilizing Stable Diffusion and SigLIP-based visual conditions. Experiments on the VITON-HD dataset demonstrate that its approach outperforms baseline methods based on pose transfer and virtual try-on while requiring fewer preprocessing and postprocessing steps. TryOffDiff not only enhances the quality of e-commerce product images but also advances the evaluation of generative models and inspires future work in high-fidelity reconstruction.

Fashion-VDM is a video diffusion model (VDM) designed to generate virtual try-on videos. This model accepts an image of a garment and a video of a person as input, aiming to produce high-quality videos showcasing the person wearing the specified clothing while preserving their identity and movements. Compared to traditional image-based virtual try-on, Fashion-VDM excels in garment detail and temporal consistency. The main advantages of this technology include: a diffusion architecture, classifier-free guidance enhancing control, progressive temporal training strategies for generating 64-frame 512px videos in one pass, and the effectiveness of joint image-video training. Fashion-VDM sets a new industry standard in the realm of video virtual try-on.

This is a prototype virtual try-on application built using Flask, Twilio's WhatsApp API, and Gradio's virtual try-on model. Users can send images via WhatsApp to try on clothes virtually, with results sent back to them. The application utilizes the Twilio Sandbox for sending and receiving WhatsApp messages and the Gradio API to handle the virtual try-on model, providing users with an innovative online shopping experience.

Google Shopping is an online shopping platform that leverages artificial intelligence technology to help users find relevant products, discover personalized options, and locate the lowest prices among over 4.5 billion product listings. It simplifies the shopping research process by providing users with intelligent displays of shopping insights through AI-generated briefs. Additionally, it includes features such as virtual try-on and AR shopping tools, enhancing users' confidence while shopping. The personalized homepage of Google Shopping showcases shoppable products and videos tailored to users' preferences, allowing for a more customized shopping experience.

Kolors Virtual Try On is a platform that utilizes advanced AI technology to provide online virtual fitting services. It helps users visualize clothing products in real environments through virtual modeling, reducing the costs associated with returns due to size discrepancies or style dissatisfaction. Users can try on clothes anywhere, anytime, enabling them to make more informed shopping choices. The platform is compatible with multiple devices, offers personalized recommendations, and ensures user data security with its privacy policy, which guarantees that all uploaded photos are securely deleted after processing.

Kolors Virtual Try-On AI is an innovative artificial intelligence technology that enables users to virtually try on clothes without physically wearing them. Users can upload personal photos and images of desired clothing items, while the AI generates realistic visualizations of the user wearing the selected outfits. This technology not only provides convenience, allowing users to experiment with different styles from the comfort of their homes but also enhances the accuracy and efficiency of the shopping experience by offering personalized fashion insights. For clothing retailers, Kolors Virtual Try-On AI delivers in-depth analysis of user try-on data, helping them understand market trends and consumer preferences, thereby optimizing product lines and marketing strategies.

Kolors Virtual Try-On AI is an online platform that utilizes artificial intelligence technology to allow users to try on clothing virtually using their uploaded photos. Through advanced computer vision algorithms and Generative Adversarial Networks (GANs), it provides realistic clothing try-on effects. This product not only transforms the traditional fitting experience but also offers innovative content creation and display methods for fashion bloggers, clothing retailers, and personal stylists. Its advantages include instant try-on results, a wide variety of clothing selections, realistic rendering effects, user privacy protection, and personalized clothing try-on experiences.

M&M VTO is a virtual try-on method that combines multiple clothing images, a text description of garment arrangements, and a person's image as input, producing a visual representation of these garments on the specified person in the given layout. The main advantages of this technology include: a single-stage diffusion model that eliminates the need for super-resolution cascades, capable of mixing multiple garments at a resolution of 1024x512 while preserving and distorting complex clothing details; an architecture design (VTO UNet Diffusion Transformer) that effectively separates denoising and person-specific features to achieve efficient identity-preserving fine-tuning strategies; control over the layout of multiple garments through text input, specifically fine-tuned for virtual try-on tasks. M&M VTO achieves state-of-the-art performance both qualitatively and quantitatively and opens up new possibilities for language-guided and multi-garment try-ons.

The Visual Try-On Chrome Extension is a Chrome browser plugin that utilizes artificial intelligence image processing technology to allow users to virtually try on clothing on any e-commerce website. The extension captures the main product image using OpenAI GPT-4, uploads the user's photo to Cloudinary, processes the image using the Kolors model from Hugging Face, and stores the results in the browser cache for better usability. It protects user privacy by not sending personal data or photos to servers, except during AI processing on Hugging Face.

Kolors Virtual Try-On is a virtual fitting application that combines artificial intelligence and augmented reality technologies to create natural and aesthetically pleasing try-on effects based on the uploaded model image and selected clothing. This product supports a complete workflow from generating model images to creating short videos, fulfilling the generation needs for e-commerce model materials.

CatVTON is a virtual try-on technology based on a diffusion model, featuring a lightweight network (total of 899.06M parameters), parameter-efficient training (49.57M trainable parameters), and simplified inference (less than 8G VRAM at 1024X768 resolution). By streamlining the network structure and inference process, it achieves quick and effective virtual fitting results, making it particularly suitable for the fashion industry and personalized recommendation scenarios.

Stable-Hair is an innovative hairstyle transfer technique that robustly transfers a diverse range of real-world hairstyles onto user-provided facial images for virtual try-ons. This method excels at handling complex and varied hairstyles, maintaining the original identity content and structure while achieving highly detailed and high-fidelity transfer effects.

ClotheDreamer is a text-guided clothing generation model based on 3D Gaussian, capable of generating high-fidelity, wearable 3D clothing assets from textual descriptions. It employs a novel representation method called Disentangled Clothe Gaussian Splatting (DCGS), allowing for separate optimization of clothing and the human body. This technology utilizes bidirectional Score Distillation Sampling (SDS) to enhance the quality of clothing and human body rendering and supports custom clothing template input. ClotheDreamer's synthesized 3D clothing can be easily applied to virtual try-on and supports physically accurate animations.

HeyBeauty is a groundbreaking AI-driven platform that leverages cutting-edge artificial intelligence to provide a virtual fitting room experience, making online shopping more interactive and accurate. This not only enhances the convenience of online shopping but also personalizes the experience to suit your unique style and preferences.

Hairpaca AI Hairstyle Generator helps you find the perfect hairstyle through ultra-realistic virtual try-on photos, all without the need for an actual haircut. With Hairpaca, you can choose from over 50 popular hairstyles, ranging from long, short, curly, straight, cute to sexy styles, to find the style that suits you best. Hairpaca supports uploading any hairstyle photo, so if our available style options don't meet your expectations, you can upload your desired hairstyle photos to your personal hairstyle library. With Hairpaca, you can get virtual try-on results in about 5 seconds, no long waiting required. Additionally, Hairpaca's over 50 hairstyle try-ons are only $9.9, allowing you to experiment with different looks at a lower cost.

IDM-VTON is a novel diffusion model for image-based virtual try-on tasks, which generates highly realistic and detailed virtual try-on images by combining the advanced semantics and low-level features of visual encoders and UNet networks. The technology enhances the authenticity of generated images through detailed text prompts and further improves fidelity and realism in real-world scenes with customized methods.

Outfit AnyOne AI is an AI-powered platform that allows users to instantly see themselves wearing any outfit virtually. It adapts to various clothing styles and body types, providing a highly realistic virtual try-on experience. Outfit AnyOne AI also allows users to create costumes for animated characters, showcasing its versatility. The platform is free to use on the website.

OOTDiffusion is an open-source virtual clothing try-on tool based on a latent diffusion model. It supports both semi-body and full-body models, enabling natural integration of clothing. Users can adjust various parameters to achieve precise control over the try-on effects, meeting diverse needs. This tool is open-source on GitHub and has received over 300 stars of attention.

The fAIshion Virtual Try-On plugin integrates AI technology to provide comprehensive pre-sales solutions for online shoppers. Its key features include AI-generated diverse try-on effects, adaptable to different body types, ages, and races, as well as AI size recommendations and automatic discount code matching, offering a personalized shopping experience.

Avumi is a fashion technology platform that provides a digital clothing try-on experience on fashion brand websites for online shoppers. With Avumi, you can allow your customers to accurately virtually try on clothing on your website, helping them make better purchase decisions.

Hairstyle AI leverages powerful artificial intelligence to help you virtually generate different hairstyles before you get a real haircut, allowing you to see which one best suits you. Suitable for both male and female hairstyles. The one-time purchase price includes 30 unique AI hairstyles, 4 different poses/styles, and 120 high-definition photos.