Apple has released several open-source artificial intelligence (AI) models this year. These are mostly small language models designed for a specific task. Adding to the list, the Cupertino-based tech giant has now released a new AI model dubbed Depth Pro. It is a vision model that can generate monocular depth maps of any image. This technology is useful in the generation of 3D textures, augmented reality (AR), and more. The researchers behind the project claim that the depth maps generated by AI are better than the ones generated with the help of multiple cameras.
Apple Releases Depth Pro AI Model
Depth estimation is an important process in 3D modelling as well as various other technologies such as AR, autonomous driving systems, robotics, and more. The human eye is a complex lens system that can accurately gauge the depth of objects even while observing them from a single-point perspective. However, cameras are not that good at it. Images taken with a single camera make it appear two-dimensional, removing depth from the equation.
So, for technologies where the depth of an object plays an important role, multiple cameras are used. However, modelling objects like this can be time-consuming and resource-intensive. Instead, in a research paper titled “Depth Pro: Sharp Monocular Metric Depth in Less Than a Second”, Apple highlighted how it used a vision-based AI model to generate zero-shot depth maps of monocular images of objects.
How the Depth Pro AI model generates depth maps
Photo Credit: Apple
To develop the AI model, the researchers used the Vision Transformer-based (ViT) architecture. The output resolution of 384 x 384 was picked, but the input and processing resolution was kept at 1536 x 1536, allowing the AI model more space to understand the details.
In the pre-print version of the paper, which is currently published in the online journal arXiv, the researchers claimed that the AI model can now accurately generate depth maps of visually complex objects such as a cage, a furry cat’s body and whiskers, and more. The generation time is said to be one second. The weights of the open-source AI model are currently being hosted on a GitHub listing. Interested individuals can run the model on the inference of a single GPU.