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features
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support

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Description

We create a three-dimensional signed distance field (SDF) and a textured field using two latent codes. DMTet is employed to derive a 3D surface mesh from the SDF, and we sample the texture field at the surface points to obtain color information. Our training incorporates adversarial losses focused on 2D images, specifically utilizing a rasterization-based differentiable renderer to produce both RGB images and silhouettes. To distinguish between genuine and generated inputs, we implement two separate 2D discriminators—one for RGB images and another for silhouettes. The entire framework is designed to be trainable in an end-to-end manner. As various sectors increasingly transition towards the development of expansive 3D virtual environments, the demand for scalable tools that can generate substantial quantities of high-quality and diverse 3D content has become apparent. Our research endeavors to create effective 3D generative models capable of producing textured meshes that can be seamlessly integrated into 3D rendering engines, thereby facilitating their immediate application in various downstream uses. This approach not only addresses the scalability challenge but also enhances the potential for innovative applications in virtual reality and gaming.

Description

Silhouette™ stands as the pioneering audience intelligence platform designed to define and engage anonymized personas through the analysis of earned media consumption, influencers, passions, personalities, and interests. By leveraging social data, Silhouette™ provides precise, actionable insights and media campaigns tailored to any specific persona or target audience. This innovative platform addresses the challenge of evaluating social influencer initiatives by linking social content engagement to tangible company revenue and various business metrics. For the first time, brands can transform their market research, marketing personas, and surveys into expansive, addressable audiences. At the heart of Silhouette™ is a comprehensive social identity graph that encompasses over 1.2 billion profiles gathered from 60 diverse platforms, more than a million websites, 300 million unique email accounts, and upwards of one billion IP addresses and mobile devices, making it a formidable tool in audience analytics. This extensive database equips brands with the capability to make informed decisions and tailor their strategies effectively.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Microsoft Excel No 
Pulsar Platform No 
Winmo No 

Integrations

Microsoft Excel Yes 
Pulsar Platform Yes 
Winmo Yes 

Pricing Details

No price information available.
Free Trial No 
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 No 
Mac No 
Linux No 
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 No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

NVIDIA

Country

United States

Website

nv-tlabs.github.io/GET3D/

Vendor Details

Company Name

StatSocial

Founded

2012

Country

United States

Website

www.statsocial.com

Product Features

Product Features

Audience Intelligence

AI / Machine Learning No 
Audience Segmentation No 
Competitive Intelligence No 
Content Tracking No 
Data Visualization No 
Data-Driven Insights No 
Filters / Search No 
Image Recognition No 
Sentiment Analysis No 
Social Listening No 
Social Media Analytics No 
Trend Tracking No 

Alternatives

Alternatives

Seed3D Reviews

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