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features
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Description

AWS Thinkbox Sequoia is an independent software solution designed for processing point clouds and creating meshes, functioning seamlessly across Windows, Linux, and macOS platforms. This application supports a wide range of industry-standard formats for point cloud and mesh data, enabling the transformation of point cloud information into a compact, quickly accessible intermediate cache format. Sequoia is equipped with intelligent workflows that maintain high-precision data effectively, allowing users to visualize either the entire point cloud or a selected subset through adaptive view-dependent techniques. With this software, users have the capability to transform, cull, and edit point cloud data, as well as to generate meshes from those point clouds and optimize the resulting models. Additionally, Sequoia facilitates the projection of images onto both points and meshes, creating mesh vertex colors and supporting Ptex or UV-based textures derived from point cloud colors and image projections. The application can export the final meshes to various industry-standard mesh file formats and is integrated with Thinkbox Deadline, allowing for the processing of point cloud data conversion, meshing, and export across network nodes, making it a versatile tool for professionals in the field. Overall, AWS Thinkbox Sequoia stands out as a comprehensive solution for those looking to enhance their workflow in point cloud processing and meshing.

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.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Thinkbox Deadline Yes 
Amazon Web Services (AWS) Yes 

Integrations

AWS Thinkbox Deadline No 
Amazon Web Services (AWS) No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/thinkbox-sequoia/

Vendor Details

Company Name

OpenAI

Founded

2015

Country

United States

Website

openai.com/research/point-e

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