Intro to Generative Models for Computer Vision Engineers

Master the foundational concepts and practical applications of GANs, VAEs, and Diffusion Models for advanced image synthesis and manipulation in computer vision.
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Foundations of Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs)

Unit 1: Introduction to Generative Models and GANs

Unit 2: Variational Autoencoders (VAEs)

Unit 3: Comparing GANs and VAEs

Diffusion Models and Practical Applications in Computer Vision

Unit 1: Understanding Diffusion Models

Unit 2: Comparing Generative Models

Unit 3: Applying Diffusion Models