Highlights: Hello and welcome to our new post. Here we are going to talk about Principal Component Analysis (PCA). In the previous post, we learned that we need to apply this method to construct a parametric face model. In order to better understand the whole process let’s remind ourselves what is PCA and how it works. The theoretical explanation of the PCA in this post is based on the YouTube video “3D Scanning & Motion…
Read more
Highlights: Hello and welcome. In the last few years, Deep fake videos become very popular on social media. In this post, we will learn the basic theory behind deep fakes, and more specifically, how we can build a 3D face model and capture a motion in the human face. In this post, we are going to review the YouTube video “3D Scanning & Motion Capture: 8. Parametric Face Models”[1]. So let’s begin! Let’s have a…
Read more
Highlights: In the previous posts we have already explored the basic GAN idea, and we have studied the guidelines for more stable training. In particular, we have analyzed the “GAN Hacks” in post 007 that was proposed in a DCGAN paper. In addition, we have implemented a simple GAN network to learn the mapping of a 1D function. Hence, to prove that the GANs are a promising family of generator architecture, we need to start…
Read more
Highlights: In the previous post, we introduced a way of training GAN models using a labeled dataset, known as Conditional Adversarial Networks (CGANs). CGANs are a revolution in the field of AI and are gaining popularity quite rapidly. One of the most famous GANs being used today is the Image2Image GAN or the Pix2Pix GAN. In this post, we will study Pix2Pix GAN in detail. Let’s begin. Tutorial overview: What is a Pix2Pix GAN? The…
Read more
Highlights: In the previous posts, we studied Deep Convolutional Generative Adversarial Networks (DCGAN). These types of conventional DCGAN architectures are trained in an unsupervised and unconditional manner. Therefore, there are no labels involved in the training process. In this post, we will see how we can train our GAN model using a labeled dataset by the use of Conditional Generative Adversarial Networks (CGAN). So, let’s begin. Tutorial overview: What are Conditional GANs? Initializing and Defining…
Read more
