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What is Hi3D?

Hi3D is a professional AI-driven 3D asset generation platform that converts 2D images into high-resolution, production-ready 3D models for industries such as gaming, animation, film, 3D printing, architecture, industrial design, fashion, and digital content creation. Developed using the Sparc3D × Ultra3D framework, the platform emphasizes high-quality geometry reconstruction, realistic surface generation, and workflow compatibility for professional creative pipelines. Unlike basic AI mesh generators that focus only on visible surfaces, Hi3D reconstructs hidden geometry and internal structural details to create complete, usable 3D assets suitable for manufacturing, rendering, and real-world production workflows. Users can upload single images or multiple reference views to generate detailed 3D models with preserved sharp edges, realistic proportions, and high-resolution textures that closely match the source imagery. The platform supports portrait-focused reconstruction capable of generating highly detailed human models with refined facial structures, skin textures, and hair-level realism at resolutions suitable for animation, collectibles, and character production. Hi3D also provides intelligent de-lighting technology that removes baked-in lighting, shadows, and environmental reflections from textures, resulting in clean PBR-ready materials that can be reused across multiple rendering and production environments. AI texturing tools automatically apply realistic 4K materials to generated or imported models, helping creators produce visually accurate assets with minimal manual editing. Multi-color segmentation capabilities simplify the preparation of models for multi-material 3D printing by automatically separating color regions into production-friendly segments.

What is GET3D?

We develop a three-dimensional signed distance field (SDF) alongside a textured field using two latent codes. To extract a 3D surface mesh from the SDF, we utilize DMTet, sampling the texture field at surface points for color information. Our training process includes adversarial losses centered on 2D images, employing a rasterization-based differentiable renderer to generate both RGB visuals and silhouettes. To differentiate between real and generated inputs, we introduce two distinct 2D discriminators—one dedicated to RGB images and the other to silhouettes. The entire system is structured to enable end-to-end training. As various industries shift towards creating expansive 3D virtual environments, the necessity for scalable tools capable of generating large volumes of high-quality and diverse 3D content becomes increasingly evident. Our research aims to develop robust 3D generative models that produce textured meshes, facilitating their seamless integration into 3D rendering engines for immediate deployment in a range of applications. This strategy not only addresses the challenge of scalability but also opens up new avenues for innovative uses in fields like virtual reality and gaming. Moreover, by enhancing the quality and diversity of 3D content, we aim to push the boundaries of creativity and interactivity within these immersive environments.

Media

No images available

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Mathmagic

Date Founded

2024

Company Location

China

Company Website

www.hitem3d.ai/

Company Facts

Organization Name

NVIDIA

Company Location

United States

Company Website

nv-tlabs.github.io/GET3D/

Categories and Features

Categories and Features

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