Chapters:
00:00 Introduction & Deep image generators
03:14 Generative Adversarial Networks
06:00 Variational Auto Encoders
16:20 Flow-based Generative Models
20:52 Strengths & Challenges

Presented at the Computer Vision Festival:
[ Ссылка ]

Abstract:
You probably heard about the cool things you can do with GANs and VAEs and some of you may even heard about flow-based generative models - but how well do you really understand how they work behind the scenes? What are their inherent strengths and weaknesses?

In this talk we will start with the basics - what are generative models and how each type of them works. Then we will dive into each one of them: the math and probabilistic interpretation, pros and cons compared to others, and see how SotA papers are handling the limitations of the vanilla method they are based on.

References + further reading: [ Ссылка ]

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