Facebook ‘3D Photos’ Tool Lets You Convert Any 2D Image Into 3D !

Facebook 3D Photos Tool Lets You Convert Any 2D Image Into 3D !

Facebook first introduced the 3D Photos feature on its social media platform that allowed users to convert any 2D image into 3D. There was one limitation to this feature though: it required a dual-camera smartphone to work

Facebook brings 3D photos feature to even those who are still rocking a single camera smartphone. Facebook is rolling out this feature to most iPhone and Android devices. 3D Photos tool now works on iPhone 7 or higher or any “recent midrange” Android smartphone.

Facebook just expanded 3D photo posting to phones that don’t actually capture depth data. Using the magic of machine learning (i.e. artificial intelligence), Facebook taught a neural network how to “infer 3D structures from 2D photos,” even if those photos were taken with a single lens camera.

How Facebook 3D Photos Tool Works?

Typically, 3D photos work by analyzing a 2D picture and separating it into multiple layers that move individually when you tilt the smartphone or scroll.
Facebook’s 3D Photos tool uses a neural network to detect how “far” each pixel in a photo is from the camera to create a three-dimensional image.

From now on, while posting a photo on Facebook, you will get the “3D Photos” option to convert your pictures into 3D.
The feature is currently rolling out on Facebook’s app. Unfortunately, Facebook hasn’t provided a full list of compatible devices. So you’ll have to wait and see if your device supports the feature in the upcoming weeks.

The technical details are complicated, but according to FB, their convoluted neural network can estimate the distance of every single pixel form the camera by using four different techniques:

-A network architecture built with a set of parameterizable, mobile-optimized neural building blocks.

-Automated architecture search to find an effective configuration of these blocks, enabling the system to perform the task in under a second on a wide range of devices.

-Quantization-aware training to leverage high-performance INT8 quantization on mobile while minimizing potential quality degradation from the quantization process.

-Large amounts of training data derived from public 3D photos.

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