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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

LTX-2.3 represents a cutting-edge AI video generation model that transforms text prompts, images, or various media inputs into high-quality videos, all while ensuring precise control over motion, structure, and the synchronization of audio and visuals. This model is a key component of the LTX series of multimodal generative tools aimed at developers and production teams seeking scalable solutions for programmatic video creation and editing. Enhancements over previous LTX versions include improved detail rendering, greater motion consistency, superior prompt comprehension, and enhanced audio quality throughout the video creation process. One of its standout features is a newly designed latent representation, utilizing an upgraded VAE trained on more refined datasets, which significantly enhances the retention of intricate details such as fine textures, edges, and small visual elements like hair, text, and complex surfaces across multiple frames. This evolution in video generation technology marks a significant leap forward for creators and professionals in the multimedia domain.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

LTX

Integrations

LTX

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

NVIDIA

Country

United States

Website

nv-tlabs.github.io/GET3D/

Vendor Details

Company Name

Lightricks

Country

Israel

Website

ltx.io/model/ltx-2-3

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Product Features

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