GET3D (Nvidia)
GET3D is NVIDIA’s AI model that generates detailed, textured 3D meshes directly from 2D images. Ideal for gaming, animation, and virtual world creation—no 3D scanning required.
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About GET3D
What is GET3D?
GET3D is an advanced generative model developed by NVIDIA that creates high-quality, textured 3D meshes directly from 2D image collections. Unlike traditional 3D modeling pipelines that require scans, sensors, or CAD tools, GET3D leverages deep learning to generate complex 3D objects—ready to use in animation, games, and virtual production.
Un bond en avant dans la création de contenu 3D
Formé à l'aide de l'apprentissage contradictoire et du rendu différentiable, GET3D peut produire divers objets aux textures et géométries réalistes. Il produit des maillages haute fidélité, à la topologie arbitraire et aux détails matériels complexes, comblant ainsi l'écart entre l'IA et les ressources 3D prêtes à la production.
How GET3D Works
Latent Space Representation
GET3D generates two distinct latent codes: one for shape (geometry) and another for texture. These are used to produce a signed distance field (SDF) and a texture field that define the 3D mesh and surface appearance.
Mesh Extraction & Texturing
Using DMTet (Deep Marching Tetrahedra), GET3D converts the SDF into a triangular mesh. Then, it queries the texture field to paint the mesh with detailed color and material features.
Training with 2D Discriminators
GET3D est entraîné à l'aide d'images et de silhouettes 2D avec pertes adverses. Le rendu différentiable permet au modèle de rétropropager les erreurs de l'espace image vers l'espace 3D, permettant ainsi l'apprentissage sans supervision 3D explicite.
Key Capabilities of GET3D
High-Quality 3D Meshes
GET3D generates textured 3D objects with fine details such as headlights, seams, fur, and reflections—making it suitable for animation and simulation tasks.
Arbitrary Topology Support
Unlike many earlier models, GET3D can generate complex, non-rigid shapes across a wide range of categories including animals, vehicles, furniture, shoes, and human avatars.
Contrôle démêlé de la forme et de la texture
GET3D separates geometry and texture into distinct latent codes. Users can independently manipulate either aspect to achieve greater control in asset generation.
Interpolation de code latent
By interpolating between latent vectors, GET3D enables smooth transitions and morphing between shapes and textures. This feature is useful for animation, asset variation, and design iteration.
Text-Guided Generation
Incorporating CLIP-based directional loss (as seen in StyleGAN-NADA), GET3D supports text-guided shape generation. Users can fine-tune outputs using natural language prompts for creative control.
Effets de matériaux et d'éclairage
When combined with DIBR++ (a hybrid renderer), GET3D can also simulate materials and lighting effects in an unsupervised fashion, enhancing realism in renders.
Applications de GET3D
Gaming & Interactive Media
Game developers can rapidly generate character models, props, and environments with consistent geometry and texture, significantly reducing manual modeling time.
Animation et production cinématographique
GET3D permet le prototypage rapide d'actifs stylisés ou photoréalistes avec une variation de conception flexible et une exportation directe dans les pipelines de rendu.
Virtual Reality & Metaverse
Ideal for VR creators, GET3D provides a scalable way to populate virtual spaces with high-quality 3D content—without the need for traditional scanning or modeling.
Commerce électronique 3D et jumeaux numériques
Retailers and industrial designers can use GET3D to visualize products in 3D from catalog images, enhancing interactive shopping and simulation workflows.
Faits saillants de la recherche
- Disentangled Geometry and Texture: Independent control of mesh shape and surface appearance.
- Adversarial Image-Based Training: No 3D labels or models required—just image collections.
- Latent Code Interpolation: Smooth transitions between different shapes and styles.
- Haute compatibilité : génère des formats de maillage standard compatibles avec Blender, Unity, Unreal et d'autres moteurs.
Project Origins & Contributors
GET3D is the result of collaborative research between NVIDIA, the University of Toronto, and the Vector Institute, presented at NeurIPS 2022. It builds on prior work like DMTet, EG3D, and DIBR++, further advancing 3D generative modeling.
Resources and Access
- GET3D GitHub & Codebase
- Research Paper PDF & arXiv
- Informations sur les citations et BibTeX disponibles sur la page du projet