GET3D (Nvidia) Features
A Generative Model of High Quality 3D Textured Shapes Learned from Images.
1. Generative Model: NVIDIA GET3D uses a generative model to learn 3D shapes from images. This model is based on a variational autoencoder (VAE) and a generative adversarial network (GAN). The VAE is used to learn a latent representation of the 3D shape from the input image, while the GAN is used to generate a 3D shape from the latent representation.
2. High Quality 3D Textured Shapes: NVIDIA GET3D is capable of generating high quality 3D textured shapes from images. The generated shapes are realistic and have detailed textures.
3. Image-Based Learning: NVIDIA GET3D uses image-based learning to learn 3D shapes from images. This allows the model to learn from a large number of images and generate realistic 3D shapes.
4. Real-Time Rendering: NVIDIA GET3D is capable of rendering 3D shapes in real-time. This allows for interactive applications such as virtual reality and augmented reality.
5. Scalable: NVIDIA GET3D is scalable and can be used to generate 3D shapes from a variety of different image sources. This makes it suitable for a wide range of applications.