How to Create 3D Product Models At Scale With artlabs

3D eCommerce

What is 3D product model generation?

3D product model generation is the process of creating a digital 3D model of a physical product. This can be done manually using 3D modeling software or automatically using AI algorithms.

There are four ways, in general, to create a digital twin of a physical product and use them as 3D assets, including CGI modeling, laser scanning, NeRF, and photogrammetry.

Each of these methods can produce highly realistic assets from the physical details of your product. They differ in quality, cost, and speed. They are relevant for developing expandable and scalable 3D creative strategies required when implementing 3D and augmented reality for eCommerce. With advances in artificial intelligence, it is possible to create a 3D asset from a few images.

How to create 3D product models at scale?

πŸ€– Neural Radiance Fields (NeRF)

Neural Radiance Fields (NeRF) is a state-of-the-art deep learning method to capture a three-dimensional (3D) scene with a neural network. A NeRF model can create a representation of a scene that is dependent on multilayer perceptrons so that we can render images from unseen angles and generate meshes.

New variations of NeRF come out every day that speed up learning and allow us to create more accurate representations of objects. With every new change, NeRF is leveling the playing field in 3D content generation by making it cheaper and more accessible.

As artlabs, we imagine a future where anyone can create and engage with 3D content from the comfort of their own homes. Today, we can train NeRF in a matter of minutes and use only a few images, but there is always a trade-off with the quality of output.

We are pushing the limits to create high-quality 3D assets using as few images as possible. To achieve this, we are putting 3D content generation at the forefront and integrating model supervision and content quality seamlessly into the pipeline.

πŸ“Έ Photogrammetry

Photogrammetry, in its most basic form, means creating reliable physical information about an object from a collection of photos of a particular product.

The most well-known photogrammetry process utilizes cameras arranged in a rig to capture a product’s pictures (approximately 80–200) from every angle, either simultaneously or in rapid succession.

To ensure scalability and portability, we use a single smartphone camera and a turntable to capture photos from various angles of a product at artlabs. Without complex workflows or dedicated training programs, point cloud data is derived from overlapping photographs and processed into a fully textured three-dimensional object.


Thanks to artlabs' automated pipeline, our algorithms provide an optimized photo-realistic 3D asset within minutes without any manual touch-up.

Photogrammetry produces unique textures that capture incredible detail and depth. Furthermore, the captured geometry is reliable, so product models are not at risk of misrepresenting the product.

What are some of the key considerations when implementing AI-powered 3D product model generation?

When implementing AI-powered 3D product model generation, it is important to consider:

βœ… The quality and quantity of training data.

βœ… The accuracy, and consistency of the resulting models.

βœ… The cost and complexity of implementing AI algorithms and infrastructure.

βœ… The compatibility of the generated models with existing design and prototyping workflows.

What are some of the benefits of using AI for 3D product model generation?

Using AI for 3D product model generation can save time and reduce costs by automating the process of creating 3D models. It can also improve the accuracy and consistency of the models, which can lead to better product design and showcase.

What are some of the challenges of using AI for 3D product model generation?

One of the main challenges of using AI for 3D product model generation is the need for large amounts of training data. This data can be difficult to obtain and may require manual labeling or preprocessing.

Additionally, AI models may struggle with complex or irregular shapes, which can lead to inaccurate models.

Fully-automated QA is a solution that can help overcome the challenges of using AI for 3D product model generation.

The solution involves training an AI algorithm to automatically check the accuracy of 3D models generated by other AI algorithms. By automating the QA process, artlabs:

πŸš€ Reduces the time and cost involved in manual QA,

πŸš€ Provides an objective and consistent evaluation of the models' quality,

πŸš€ Improves the accuracy of 3D models generated by AI algorithms.

What industries can benefit from AI-powered 3D product model generation?

Many industries can benefit from AI-powered 3D product model generation, including retail, footwear, automotive, furniture, and consumer products.

Any industry that relies on product design and showcase can benefit from the increased speed and accuracy of AI-powered 3D modeling.

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