Category: Deep Learning

#004 3D Face Modeling – 3D Scanning & Motion Capture: Parametric Face Models

12.12.2022

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

09.12.2022

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…
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#007 How to implement GAN Hacks to Train Stable Models?

05.04.2022

Highlights: In this post, we are going to learn several hacks that we can use to train stable GAN models. First, we are going to provide a quick recap of the GANs theory, and then, we are going to talk about challenges when training GANs. After that, we will provide solutions for these challenges in Python. So, let’s begin with our post. Tutorial Overview: Challenges when training GANs Heuristics for Training Stable GANs Architecture for guidelines…
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#006 GANs – How to Develop a 1D GAN from Scratch

05.04.2022

Highlight: In this post, we will briefly review the theory behind Generative Adversarial Networks and then we will learn to implement that knowledge in PyTorch. We will actually build our first GAN from scratch so that all the details are demystified. Initially, we will start with generator modeling or faking a simple 1D function (sine wave). In the later posts, we will build on the fundamental GAN architecture presented in this post.  Tutorial Overview: GAN…
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# 020 Overview of Semantic Segmentation methods

08.11.2021

Highlights: Hello and welcome back. In this post, we will see how we can use Neural Networks for the segmentation task. To be more precise, it will be about Semantic Segmentation. The goal of Semantic Segmentation is to label each pixel of an image with a corresponding class. We will cover some of the most popular Deep Learning models for segmentation: Fully Convolutional Neural Network SegNet U-Net Tutorial Overview: What is Semantic Segementation? Types of segmentations Fully Convolutional Neural…
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