2021年11月22日 · A picture worth a thousand words now takes just three or four words to create, thanks to GauGAN2, the latest version of NVIDIA Research’s wildly popular AI painting demo. The deep learning model behind GauGAN allows anyone to channel their imagination into photorealistic masterpieces — and it’s easier than ever.

2020年6月17日 · Over the years, NVIDIA researchers have contributed several breakthroughs to GANs. This new project called StyleGAN2, presented at CVPR 2020, uses transfer learning to generate a seemingly infinite numbers of portraits in an infinite variety of painting styles. The work builds on the team’s previously published StyleGAN project.

2018年6月19日 · Researchers from NVIDIA, led by Ting-Chun Wang, have developed a new deep learning-based system that can generate photorealistic images from high-level labels, and at the same time create a virtual environment that allows the user to modify a scene interactively.

NVIDIA AI Foundation offers an easy-to-use interface to quickly experience generative AI models from your browser without any setup. After you explore the model, you can customize it and take it to production with NVIDIA AI Enterprise.

2019年3月18日 · But a deep learning model developed by NVIDIA Research can do just the opposite: it turns rough doodles into photorealistic masterpieces with breathtaking ease. The tool leverages generative adversarial networks, or GANs, …

2024年7月3日 · NVIDIA’s GauGAN, named after post-Impressionist painter Paul Gauguin, is an AI demo for photorealistic image generation. Built by NVIDIA Research, it directly led to the development of the NVIDIA Canvas app — and can be experienced for …

NVIDIA 的 GauGAN 是一种能够利用 AI 将手绘草图转换为写实风艺术作品的模型，可为 NVIDIA Canvas 应用 提供支持。 GAN 是一种深度学习模型，它包含两个互补的神经网络：一个生成器和一个判别器。 这两个神经网络会相互竞争。 生成器试图创建栩栩如生的写实图像，而判别器则试图区分真实图像和生成图像。 随着这两个神经网络不断相互挑战，GAN 在绘制写实的图像方面的能力愈发纯熟。 GAN 擅长理解复杂的数据模式并创建高质量结果。 它们被用于多种应用，包 …

3D-aware Generative Adversarial Networks (GANs) have shown remarkable progress in learning to generate multi-view-consistent images and 3D geometries of scenes from collections of 2D images via neural volume rendering.

NVIDIA Research 的最新 AI 模型可谓生成式对抗网络（GAN）领域的“神童”。 相较于典型的 GAN，它只需要基于极少量的学习材料，就能学习诸如模仿著名画家和重建癌症组织图像这样复杂的技能。

EditGAN is the first GAN-driven image editing framework, which simultaneously (i) offers very high-precision editing, (ii) requires only very little annotated training data (and does not rely on external classifiers), (iii) can be run interactively in real time, (iv) allows for straightforward compositionality of multiple edits, (v) and works ...