Few-shot 3D Shape Generation

Understand

Realistic and diverse 3D shape generation is helpful for a wide variety of applications such as virtual reality, gaming, and animation.

• Modern generative models, such as GANs and diffusion models, learn from large-scale datasets and generate new samples following similar data distributions.
• However, when training data is limited, deep neural generative networks overfit and tend to replicate training samples.
• Prior works focus on few-shot image generation to produce high-quality and diverse results using a few target images.