Which of the following are use cases of generative adversarial networks?
Generative Adversarial Networks (GANs) are widely used in several creative and image generation tasks, including:
A . Photo repair: GANs can be used to restore missing or damaged parts of images.
B . Generating face images: GANs are known for their ability to generate realistic face images.
C . Generating a 3D model from a 2D image: GANs can be used in applications where 2D images are converted into 3D models.
D . Generating images from text: GANs can also generate images based on text descriptions, as seen in tasks like text-to-image synthesis.
All of the provided options are valid use cases of GANs.
HCIA AI
Deep Learning Overview: Discusses the architecture and use cases of GANs, including applications in image generation and creative content.
AI Development Framework: Covers the role of GANs in various generative tasks across industries.
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