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Description
Recent advancements in text-based 3D object generation have yielded encouraging outcomes; however, leading methods generally need several GPU hours to create a single sample, which is a stark contrast to the latest generative image models capable of producing samples within seconds or minutes. In this study, we present a different approach to generating 3D objects that enables the creation of models in just 1-2 minutes using a single GPU. Our technique initiates by generating a synthetic view through a text-to-image diffusion model, followed by the development of a 3D point cloud using a second diffusion model that relies on the generated image for conditioning. Although our approach does not yet match the top-tier quality of existing methods, it offers a significantly faster sampling process, making it a valuable alternative for specific applications. Furthermore, we provide access to our pre-trained point cloud diffusion models, along with the evaluation code and additional models, available at this https URL. This contribution aims to facilitate further exploration and development in the realm of efficient 3D object generation.
Description
Retro Diffusion stands out as a distinctive platform created by artists with the aim of enhancing your artistic endeavors, simplifying the process of pixel art creation. Every tool is meticulously designed to spark creativity while alleviating common obstacles, allowing you to concentrate on making art instead of worrying about the details. With its AI-driven image generation capabilities, users can create production-ready artwork in mere moments. Accessible via contemporary web browsers, Retro Diffusion encourages artists to elevate their work to new heights. This innovative platform not only streamlines the creation of pixel art but also empowers users to unleash their full creative potential by minimizing stress and frustration. Dive into the world of Retro Diffusion and experience the joy of art-making in a whole new way.
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Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
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Windows
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Linux
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Chromebook
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Online Support
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Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
OpenAI
Founded
2015
Country
United States
Website
openai.com/research/point-e
Vendor Details
Company Name
Retro Diffusion
Website
www.retrodiffusion.ai/