AI Conversion of Text-to-3D Model

By Shaan Khan

3D Modelling is the process of creating digital objects with 3D shapes and depth that simulate physical objects in real life. 3D Modelling can bring to life objects tied to fiction and described only through books that were birthed through imagination.

The process of creating 3D objects has historically been a complicated task that requires computational power and skilled workers in a field dedicated to 3D Modelling. It’s not for everyone. 3D Modelling projects can take months or years to complete—with iconic movies ‘The Incredibles 2’ and ‘Toy Story 4’ that required 3D modelling taking over five years to complete.

Commercial industries continue to adopt 3D modelling to scale up businesses, but traditional methods are proven to be expensive and time-consuming—dependant on the quality of 3D modelling requested. 

In 2022, we began to see the rise of ‘Text-to-3D Model’ AI Convertors that now give people the ability to develop 3D models with descriptions they write. In retrospect, there hasn’t been a greater time for the emergence of AI-Generated 3D models than now. Most hardware today has the computational power to create 3D models and render them for applications and media. This makes AI-Generated 3D modelling more scalable than traditional methods since it is more accessible in terms of hardware and has a low skill bar of entry.

With streamlined capacity, more niche businesses and entrepreneurs will take advantage of the system to compete with high-budget companies that have been benefiting from 3D Modelling. The industry-centric tasks that will benefit include some of the following:

• Video Game Development: The biggest entertainment industry in market cap is gaming. This billion-dollar industry has led games such as Grand Theft Auto 5 to make $1 billion in retail sales faster than any other entertainment release historically. The demand for video games is high. Still, as developers aim to advance gaming to meet with growing expectations, development is becoming more difficult, costly, time-consuming and with more room for errors.

• Simulations: A broad-stroke use-case for many industries, simulations are made to create digital renditions of realistic settings and items with 3D objects. Simulations allow professionals to visualise an accurate concept to aid them with their IRL developments and missions. Industries that benefit from simulations include manufacturing, engineering, aerospace, military, healthcare, urban planning, architecture, etc.

• Multimedia: The internet is gradually developing into a virtual reality space dictated by 3D Objects. Programmers and Media Professionals require 3D objects for applications, websites and content as the metaverse initiative continues to expand online. For the internet to be transformed into a virtual and augmented reality space, it will require countless users creating 3D Objects, and AI Generation presents itself as the most scalable solution.

The Current Landscape of Text-to-3D Object AI Generation:

In 2023, the market space for Text-to-3D Objects is being fought over between OpenAI applications and Google’s DreamFusion. OpenAI is a platform that has birthed many popular AI-generated software that has surfaced recently, with the most popular being ChatGPT and Dall-E. Since OpenAI is an open platform for developers to create AI with OpenAI source code, many unique creations have surfaced, including Text-to-3D Object generation.

OpenAI has positioned itself as a direct competitor to Google since the platform aims to automate many of Google’s tasks. However, Google is now building its own product line of AI-generated software, including DreamFusion—a Text-to-3D Object AI Generator.

The key differences between OpenAI 3D Object Generators and DreamFusion are the following:

• OpenAI: 3D AI Generators within this branch, such as Point-E, use synthetic technology that taps into OpenAI’s artificial intelligence full of cultural object data to use as context when generating a 3D object based on a text description. The technology first creates a 2D image of the description and then makes points of geometry to expand the image into a 3D object using the cultural context from OpenAI.

• Google: DreamFusion expands upon Google’s previous technology of Dream Fields, the traditional process of 3D modelling that utilises high-fidelity cameras to capture objects and process them into 3D models. DreamFusion uses the 3D model database from Dream Fields as cultural context for DreamFusion’s Text-to-3D Object feature.

While Google DreamFusion is limited to the database of Dream Fields, it has access to a library of high-quality 3D objects that have now become streamlined through AI. OpenAI is the more efficient platform for Text-to-3D Object generation and doesn’t require a library of pre-existing 3D models to generate 3D models. 

However, the quality of OpenAI 3D objects is currently not on par with DreamFusion. Still, as OpenAI evolves, it could boast DreamFusion generation fidelity but with a limitless data pool to extract from.

The Future Landscape of Text-to-3D Object AI Generation:

With all the advantages provided by AI-Generated Text-to-3D Objects, it still has a long way to go at presenting the same level of craftsmanship seen in 3D objects used for cinematic and ultra-realistic content. Synthesis AI could be one of the first AI platforms to reach the high-tier status of 3D modelling. Launched in 2023, Synthesis AI is dedicated to the creation of digital humans to be used in virtual reality, gaming and simulations.

Synthesis AI combines Generative AI with cinematic VFX pipelines to create photorealistic 3D objects of humans. The importance of creating digital humans is the future of the internet is calling for all humans to be represented by digital humans in the metaverse. Instead of websites, applications and video game developers creating avatars for users, AI generators such as Synthesis AI gives all humans access to produce high-fidelity digital humans.

The future of the internet wants to create a currently complicated visual landscape, and AI is the way to achieve this for mass adoption. Critics fear AI adoption will lead to job cuts within the 3D Modelling sector. However, 3D modelling artists can use Text-to-3D Objects to expand and scale up their creations.

Overall, Text-to-3D Objects will help all people conceptualise and visualise their ideas more clearly, especially for visual projects. As we continue to push the internet towards a more visual and immersive direction that’s sensory engaging, then tools such as Text-to-3D Objects are a necessity to scale up for this complex future that will explode in population with websites, applications, video games, media and simulations that are purposefully built around 3D Objects.