The successor to the GauGAN model, known as GauGAN2, enables users to craft authentic landscape photos. GauGAN2 can translate written descriptions into high-quality images that can be further customized.
Powered by deep learning, GauGAN2 empowers individuals to transform their concepts into photorealistic artworks. Simply input a phrase like "sunset at a beach," and witness as the AI swiftly generates the corresponding scene. By introducing new descriptors like "sunset on a rocky beach," or by substituting "sunset" with "afternoon" or "rainy day," the model, founded on generative adversarial networks, promptly adapts the image. Leveraging a neural network trained on a vast dataset of 10 million nature photographs, the NVIDIA GauGAN2 creates authentic visuals based on user descriptions. Following this, users can manually enhance the image by adding new elements through sketching.
With a single click, users can formulate a segmentation map, a high-level overview of the scene's elements. They can then transition to sketching, refining the image with preliminary drawings labeled sky, tree, rock, and river, allowing the intelligent paintbrush to merge these sketches into captivating masterpieces.
Key Features of GauGAN2
GauGAN2 stands out as one of the initial demonstrations to unite various modes – text, semantic segmentation, sketch, and style – within a unified GAN framework. It streamlines the process of translating an artist's vision into a high-quality AI-generated image. For instance, users can input a simple word to generate the primary features and subject of the image, such as a snow-capped mountain range, without having to sketch every detail of an imagined landscape. This starting point can be further adjusted using sketches to alter elements like mountain height or cloud coverage. Its creative potential extends beyond realism, allowing artists to craft surreal settings.
The researchers trained GauGAN2's AI model on a massive dataset of high-quality landscape photos utilizing the powerful NVIDIA Selene supercomputer. This supercomputer, an NVIDIA DGX SuperPOD system, ranks among the world's top ten.
In comparison to existing models designed specifically for text-to-image or segmentation map-to-image applications, GauGAN2's neural network generates a broader array of higher quality images.
GauGAN2 enables users to rapidly and precisely construct scenarios using text prompts and sketches. Moreover, GauGAN2 serves as a robust tool for crafting photorealistic art by seamlessly integrating segmentation mapping, inpainting, and text-to-image production within a single model. The GauGAN2 model operates on generative adversarial networks (GANs).
GauGAN2 presents a glimpse into the future potential of potent image-generation tools for artists. The NVIDIA Canvas, an application built on GauGAN technology, is freely available to all NVIDIA RTX GPU users. Deep learning models utilized in GauGAN2 effortlessly transform written phrases or sentences into visually striking artworks. Thanks to GauGAN2, the latest advancement in NVIDIA Research's AI painting demo, creating an image that speaks a thousand words now requires just three or four sentences.