Point-E Description
Although recent work on text conditional 3D object creation has shown promising results the state-ofthe-art methods require multiple GPU hours to produce a sample. This is in stark contrast with state-of-the art generative image models that produce samples within seconds or minutes. In this paper we explore an alternative 3D object generation method that produces 3D models within 1-2 minutes using a single GPU. Our method generates a single synthetic image using a text to image diffusion model, and then produces a point cloud in 3D using a second diffuser model that conditions the generated images. Our method is still behind the current state-of-the art in terms of sample quality but it is up to two orders faster to sample, which can be a good trade-off depending on the use case. Our pre-trained diffusion models are available at this https URL, along with evaluation code and models.
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Company Details
Company:
OpenAI
Year Founded:
2015
Headquarters:
United States
Website:
openai.com/research/point-e
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Product Details
Platforms
SaaS
Type of Training
Documentation
Customer Support
Online
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