Author: datahacker.rs

#011 3D Face Modeling – Capture, Learning, and Synthesis of 3D Speaking Styles – VOCA

Highlights: Hello and welcome back! We will continue our post series on talking faces. In this post, we will explore, the so-called, face animation. That is, we will not be focussed on face photo-realism, but on a digital avatar. So, let’s begin. Let’s have a look at the image below. Here we can see the difference between the animated character and a realistic 3D digital human. In this post, we will explore a model called…
Read more

#010 3D Face Modeling – Gentle Introduction to 3D rotations on a cube

Highlights: Hello and welcome. In this post, we will see examples and how we can rotate 3D objects. We will see how we can rotate a 3D cube around each axis, the \(x, y, z\) axes. Definition of the cube Now, we will do an example in Python by creating a 3D object which will consist of points with 3 dimensions. This 3D object will be a cube and we will rotate it around the…
Read more

#006 3D Face Modeling – A Morphable Model for the synthesis of 3D Faces

Highlights: Hello and welcome. In this post, we shall describe a modeling technique for 3D textured faces. By converting a set of 3D face models’ shapes and textures into a vector space representation, we will be able to create a morphable face model. By creating linear combinations of face models, new faces and facial expressions can be generated. So, let us begin this journey! 3D Database of Faces (Cyberware TM) In order to create 3D…
Read more

#007 3D Face Modeling – 3DMM model fitting in Python

Highlights: In this post, we will see how we can create a face model just from an input image using PyTorch. For this 3D model, we will obtain all the parameters which we can later play with. So, let’s begin with our post. Data preparation The first step for running the code is cloning the GitHub repository from Ascust, which has very well-explained instructions for running the code. The next step is to download the…
Read more

GANs #004 Variational Autoencoders – in-depth explained

Highlight: In this post, we will be discussing Variational Autoencoders (VAE). In order to fully understand the underlying ideas, we need to have a basic understanding of traditional Autoencoders. Luckily, we have already written about them in our previous posts. This post will consist of several topics. First, we will review autoencoders. Then, we will give some review of basic probability concepts. Next, we will explain what Kullback Leibler divergence is. In addition, we will…
Read more