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features
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support

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Description

Crafiq serves as a comprehensive AI-driven platform dedicated to the creation of various digital assets, including 2D and 3D visuals, videos, and audio, streamlining the content generation process for creators. By combining cutting-edge AI models, the platform empowers users to efficiently produce and refine high-quality assets, whether they be vibrant 2D illustrations, intricate 3D models, engaging video snippets, or captivating audio elements. Specifically for 2D creations, Crafiq offers a range of functionalities such as generation, editing, inpainting, reframing, upscaling, background removal, and refinement, utilizing advanced models like FLUX, Nano Banana, GPT Image, and Seedream. When it comes to 3D asset production, the platform enables the transformation of images into detailed, game-ready meshes, leveraging models such as Hunyuan3D, Trellis, and Rodin among others. Additionally, Crafiq provides tools for creating isometric or top-down tiles, 360° panoramas for environmental settings, pixel-perfect assets with consistent color schemes, brief video clips, seamless loopable character animations, original sound effects, music compositions, and realistic voiceovers, ensuring a versatile creative experience for users. Ultimately, Crafiq stands out as an invaluable resource for creators aiming to enhance their workflow and bring their artistic visions to life with unprecedented speed and efficiency.

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.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

FLUX.2 Yes 
GPT Image 1.5 Yes 
Hunyuan3D 2.0 Yes 
Nano Banana 2 Yes 
Nano Banana 2 Lite Yes 
Seedream Yes 
Trellis Yes 

Integrations

FLUX.2 No 
GPT Image 1.5 No 
Hunyuan3D 2.0 No 
Nano Banana 2 No 
Nano Banana 2 Lite No 
Seedream No 
Trellis No 

Pricing Details

$10 per month
Free Trial No 
Free Version Yes 

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

Vendor Details

Company Name

Crafiq

Country

United States

Website

crafiq.ai/

Vendor Details

Company Name

NVIDIA

Country

United States

Website

nv-tlabs.github.io/GET3D/

Product Features

Product Features

Alternatives

Alternatives

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