Explore the world of Generative Adversarial Networks (GANs) for image synthesis and translation in this 46-minute video workshop by Dr. Jan Kautz. Dive into the complexities of GANs, their applications in generating conditional facial features, and recent advancements in the field. Learn to identify and explain essential components of GANs, including Deep Convolutional versions, modify existing implementations, and design GANs for novel applications. Gain insights into recent improvements in GAN loss functions and understand the challenges of training these models. Cover topics such as image translation, conditional GANs, supervised vs. unsupervised learning, unimodal vs. multimodal approaches, and the shared latent space assumption. Ideal for data scientists, researchers, and software developers familiar with deep learning tools like Keras and TensorFlow, this workshop provides a comprehensive overview of GAN technology and its potential in image manipulation and generation.