Researchers at NVIDIA have come up with a clever machine learning technique for taking 2D images and fleshing them out into 3D models. Normally this happens in reverse--these days, it's not all that difficult to take a 3D model and flatten it into a 2D image. But to create a 3D model without feeding a system 3D data is far more challenging. But there's information to be gained from doing the opposite--a model that could infer a 3D object from a 2D image would be able to perform better object tracking, for example.," What the researchers came up with is a rendering framework called DIB-R, which stands for differentiable interpolation-based renderer.

Nvidia researchers have published a paper describing a rendering framework that can produce 3D objects from 2D images. Not only that, due to the power of machine learning and AI, the tech does a good job of predicting the correct shape, colour, texture and lighting of the real-life 3D objects. The research could have important impacts in machine vision with depth perception, for robotics, self driving cars, and more. The full research paper, typically dryly entitled Learning to Predict 3D Objects with an Interpolation-Based Renderer, is available as a PDF by clicking the link. A new rendering framework called DIB-R, a differentiable interpolation-based renderer, is the main topic of the paper.

A method of machine learning has proven capable of turning 2D images into 3D models. Created by researchers at multi-million-dollar GPU manufacturer NVIDIA, the framework shows that it is possible to infer shape, texture, and light from a single image, in a similar way to the workings of the human eye. "Close your left eye as you look at this screen. Now close your right eye and open your left," writes NVIDIA PR specialist Lauren Finkle on the company blog, "you'll notice that your field of vision shifts depending on which eye you're using. That's because while we see in two dimensions, the images captured by your retinas are combined to provide depth and produce a sense of three-dimensionality." Termed a differentiable interpolation-based renderer, or DIB-R, the NVIDIA rendering framework has the potential to aid, and accelerate various areas of 3D design and robotics, rendering 3D models in a matter of seconds.

Turning a sketch or photo of an object into a fully realized 3D model so that it can be duplicated using a 3D printer, played in a video game, or brought to life in a movie through visual effects, requires the skills of a digital modeler working from a stack of images. But Nvidia has successfully trained a neural network to generate fully-textured 3D models based on just a single photo. We've seen similar approaches to automatically generating 3D models before, but they've either required a series of photos snapped from many different angles for accurate results or input from a human user to help the software figure out the dimensions and shape of a specific object in an image. Neither are wrong approaches to the problem; any improvements made to the task of 3D modeling are welcome as they make such tools available to a wider audience, even those lacking advanced skills. But they also limit the potential uses for such software. At the annual Conference on Neural Information Processing Systems which is taking place in Vancouver, British Columbia, this week, researchers from Nvidia will be presenting a new paper--"Learning to Predict 3D Objects with an Interpolation-Based Renderer"--that details the creation of a new graphics tool called a differentiable interpolation-based renderer, or DIB-R, for short, which sounds only slightly less intimidating.

Would you like to turn your child's drawings into real? It'd be the best gift to give your child their own work of art. If you'd like to do it, then here's a great invention for you. NVIDIA researchers invented Artificial Intelligence, which is called DIB-R, that can turn 2D images into 3D models. The machine can predict what would the 2D image look like in three dimensions and create a 3D model, by taking lighting, texture, and depth into the consideration. SEE ALSO: NVIDIA LETS YOU RECREATE YOUR DOG'S SMILE ON ANOTHER ANIMAL WITH NEW APP The model will be presented by the NVIDIA researchers at the annual Conference on Neural Information Processing Sytems (NeurIPS), Vancouver.

NVIDIA has built an artificial intelligence that can create a detailed 3D model of an object -- all from just a single image of it. The system, dubbed the "differentiable interpolation-based renderer" (DIB-R), is the first AI to manage that feat, and also produces its models in less than 100 milliseconds -- a capability that NVIDIA says could make the AI ideal for use in autonomous robots. According to a NVIDIA blog post, it takes about two days to train DIB-R to produce models of certain type of object. After training the AI on photos of birds, for example, the researchers could feed it a photo of a bird it hadn't seen before, and the system could speedily produce a 3D model of the bird predicting its shape, color, and texture. NVIDIA opined that autonomous robots could use DIB-R to improve their depth perception, allowing them to navigate their 3D environments more easily.

What if developing a 3D gaming world were as easy as snapping pics with your phone? Nvidia researchers recently developed an AI system capable of predicting a complete 3D model from any 2D image. Called "DIB-R," the AI takes a picture of any 2D object – an image of a bird, for example – and predicts what it would look like in three dimensions. This prediction includes lighting, texture, and depth. DIB-R stands for differentiable interpolation-based renderer, meaning it combines what it "sees," a 2D image, and makes inferences based on a 3D "understanding" of the world.

Close your left eye as you look at this screen. Now close your right eye and open your left -- you'll notice that your field of vision shifts depending on which eye you're using. That's because while we see in two dimensions, the images captured by your retinas are combined to provide depth and produce a sense of three-dimensionality. Machine learning models need this same capability so that they can accurately understand image data. NVIDIA researchers have now made this possible by creating a rendering framework called DIB-R -- a differentiable interpolation-based renderer -- that produces 3D objects from 2D images. The researchers will present their model this week at the annual Conference on Neural Information Processing Systems (NeurIPS), in Vancouver.