ModelScope

ModelScope

Alibaba Cloud
Point-E

Point-E

OpenAI
+
+

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About

This model is based on a multi-stage text-to-video generation diffusion model, which inputs a description text and returns a video that matches the text description. Only English input is supported. This model is based on a multi-stage text-to-video generation diffusion model, which inputs a description text and returns a video that matches the text description. Only English input is supported. The text-to-video generation diffusion model consists of three sub-networks: text feature extraction, text feature-to-video latent space diffusion model, and video latent space to video visual space. The overall model parameters are about 1.7 billion. Support English input. The diffusion model adopts the Unet3D structure, and realizes the function of video generation through the iterative denoising process from the pure Gaussian noise video.

About

While recent work on text-conditional 3D object generation has shown promising results, the state-of-the-art methods typically require multiple GPU-hours to produce a single sample. This is in stark contrast to state-of-the-art generative image models, which produce samples in a number of seconds or minutes. In this paper, we explore an alternative method for 3D object generation which produces 3D models in only 1-2 minutes on a single GPU. Our method first generates a single synthetic view using a text-to-image diffusion model and then produces a 3D point cloud using a second diffusion model which conditions the generated image. While our method still falls short of the state-of-the-art in terms of sample quality, it is one to two orders of magnitude faster to sample from, offering a practical trade-off for some use cases. We release our pre-trained point cloud diffusion models, as well as evaluation code and models, at this https URL.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Users interested in an open source text-to-video AI video generation model

Audience

Anyone searching for a system for generating 3D point clouds from complex prompts

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Alibaba Cloud
China
modelscope.cn/

Company Information

OpenAI
Founded: 2015
United States
openai.com/research/point-e

Alternatives

Alternatives

Shap-E

Shap-E

OpenAI
RODIN

RODIN

Microsoft

Categories

Categories

Integrations

01.AI
CodeQwen
GLM-4.5
Qwen
Qwen-7B
Qwen-Image
Qwen2
Qwen2-VL
Qwen2.5
Qwen2.5-1M
Qwen2.5-Coder
Qwen2.5-Max
Qwen2.5-VL
Qwen3
Yi-Large

Integrations

01.AI
CodeQwen
GLM-4.5
Qwen
Qwen-7B
Qwen-Image
Qwen2
Qwen2-VL
Qwen2.5
Qwen2.5-1M
Qwen2.5-Coder
Qwen2.5-Max
Qwen2.5-VL
Qwen3
Yi-Large
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