The cost of capturing the number of multi-view images necessary to render a showroom’s worth of cars, or a street’s worth of buildings, can be prohibitive. With Omniverse Connectors, developers can use their preferred 3D applications in Omniverse to simulate complex virtual worlds with real-time ray tracing.īut not every creator has the time and resources to create 3D models of every object they sketch. From Flat Tire to Racing KITTĬreators in gaming, architecture and design rely on virtual environments like the NVIDIA Omniverse simulation and collaboration platform to test out new ideas and visualize prototypes before creating their final products.
The research behind GANverse3D will be presented at two upcoming conferences: the International Conference on Learning Representations in May, and the Conference on Computer Vision and Pattern Recognition, in June. “Because we trained on real images instead of the typical pipeline, which relies on synthetic data, the AI model generalizes better to real-world applications,” said NVIDIA researcher Jun Gao, an author on the project.
Instead, with no aid from 3D assets, “We turned a GAN model into a very efficient data generator so we can create 3D objects from any 2D image on the web,” said Wenzheng Chen, research scientist at NVIDIA and lead author on the project. Previous models for inverse graphics have relied on 3D shapes as training data.
When imported as an extension in the NVIDIA Omniverse platform and run on NVIDIA RTX GPUs, GANverse3D can be used to recreate any 2D image into 3D - like the beloved crime-fighting car KITT, from the popular 1980s Knight Rider TV show. This model can be used with a 3D neural renderer that gives developers control to customize objects and swap out backgrounds.
Once trained on multi-view images, GANverse3D needs only a single 2D image to predict a 3D mesh model. These multi-view images were plugged into a rendering framework for inverse graphics, the process of inferring 3D mesh models from 2D images. To generate a dataset for training, the researchers harnessed a generative adversarial network, or GAN, to synthesize images depicting the same object from multiple viewpoints - like a photographer who walks around a parked vehicle, taking shots from different angles. This capability could help architects, creators, game developers and designers easily add new objects to their mockups without needing expertise in 3D modeling, or a large budget to spend on renderings.Ī single photo of a car, for example, could be turned into a 3D model that can drive around a virtual scene, complete with realistic headlights, tail lights and blinkers. NVIDIA Research is revving up a new deep learning engine that creates 3D object models from standard 2D images - and can bring iconic cars like the Knight Rider’s AI-powered KITT to life - in NVIDIA Omniverse.ĭeveloped by the NVIDIA AI Research Lab in Toronto, the GANverse3D application inflates flat images into realistic 3D models that can be visualized and controlled in virtual environments.