WorldClaw

WorldClaw

Tencent
+
+

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About

Text2Mesh produces color and geometric details over a variety of source meshes, driven by a target text prompt. Our stylization results coherently blend unique and ostensibly unrelated combinations of text, capturing both global semantics and part-aware attributes. Our framework, Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which conform to a target text prompt. We consider a disentangled representation of a 3D object using a fixed mesh input (content) coupled with a learned neural network, which we term neural style field network. In order to modify style, we obtain a similarity score between a text prompt (describing style) and a stylized mesh by harnessing the representational power of CLIP. Text2Mesh requires neither a pre-trained generative model nor a specialized 3D mesh dataset. It can handle low-quality meshes (non-manifold, boundaries, etc.) with arbitrary genus, and does not require UV parameterization.

About

WorldClaw is a fully agentic, coarse-to-fine framework for generating large-scale, freely explorable, and editable 3D open worlds from open-ended text prompts. Rather than synthesizing an entire world in a single pass, it follows a global-to-regional construction strategy that maintains coherent spatial organization while adding rich local detail. Planning agents first translate a prompt into a structured scene specification covering regions, terrain, assets, materials, visual style, and spatial relationships. It builds a globally coherent terrain foundation using semantic layouts, reusable assets, generative or procedural materials, and region-aware height fields. For regions requiring greater detail, WorldClaw creates terrain-conditioned compositions, reconstructs editable textured meshes, and recovers their placement within the scene. Render-based agents further refine terrain geometry, objects, appearance, arrangements, and contacts with the environment.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Organizations that need a complete AI 3D Model Generator solution

Audience

3D creators, game developers, researchers, and creative technology teams seeking to generate large-scale, explorable, and editable 3D worlds from open-ended text prompts

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Text2Mesh
threedle.github.io/text2mesh/

Company Information

Tencent
Founded: 1998
China
tencent-hunyuan.github.io/Hunyuan3D-WorldClaw/

Alternatives

Alternatives

Quick Terrain Modeler

Quick Terrain Modeler

Applied Imagery
HunyuanWorld

HunyuanWorld

Tencent
FLUX.2 [max]

FLUX.2 [max]

Black Forest Labs
Irrimaker

Irrimaker

Senninger Irrigation

Categories

Categories

Integrations

No info available.

Integrations

No info available.
Claim Text2Mesh and update features and information
Claim Text2Mesh and update features and information
Claim WorldClaw and update features and information
Claim WorldClaw and update features and information