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Modern Computer Vision with PyTorch

You're reading from  Modern Computer Vision with PyTorch

Product type Book
Published in Nov 2020
Publisher Packt
ISBN-13 9781839213472
Pages 824 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
V Kishore Ayyadevara V Kishore Ayyadevara
Profile icon V Kishore Ayyadevara
LinkedIn
V Kishore Ayyadevara leads a team focused on using AI to solve problems in the healthcare space. He has 10 years' experience in data science, solving problems to improve customer experience in leading technology companies. In his current role, he is responsible for developing a variety of cutting edge analytical solutions that have an impact at scale while building strong technical teams. Prior to this, Kishore authored three books — Pro Machine Learning Algorithms, Hands-on Machine Learning with Google Cloud Platform, and SciPy Recipes. Kishore is an active learner with keen interest in identifying problems that can be solved using data, simplifying the complexity and in transferring techniques across domains to achieve quantifiable results.
See other products by V Kishore Ayyadevara
Yeshwanth Reddy Yeshwanth Reddy
Profile icon Yeshwanth Reddy
LinkedIn
Yeshwanth is a highly accomplished data scientist manager with 9+ years of experience in deep learning and document analysis. He has made significant contributions to the field, including building software for end-to-end document digitization, resulting in substantial cost savings. Yeshwanth's expertise extends to developing modules in OCR, word detection, and synthetic document generation. His groundbreaking work has been recognized through multiple patents. He also created a few Python libraries. With a passion for disrupting unsupervised and self-supervised learning, Yeshwanth is dedicated to reducing reliance on manual annotation and driving innovative solutions in the field of data science.
See other products by Yeshwanth Reddy
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Table of Contents (25) Chapters

Preface Section 1 - Fundamentals of Deep Learning for Computer Vision
Artificial Neural Network Fundamentals PyTorch Fundamentals Building a Deep Neural Network with PyTorch Section 2 - Object Classification and Detection
Introducing Convolutional Neural Networks Transfer Learning for Image Classification Practical Aspects of Image Classification Basics of Object Detection Advanced Object Detection Image Segmentation Applications of Object Detection and Segmentation Section 3 - Image Manipulation
Autoencoders and Image Manipulation Image Generation Using GANs Advanced GANs to Manipulate Images Section 4 - Combining Computer Vision with Other Techniques
Training with Minimal Data Points Combining Computer Vision and NLP Techniques Combining Computer Vision and Reinforcement Learning Moving a Model to Production Using OpenCV Utilities for Image Analysis Other Books You May Enjoy Appendix

Generating deep fakes

We have learned about two different image-to-image tasks so far: semantic segmentation with UNet and image reconstruction with autoencoders. Deep fakery is an image-to-image task that has a very similar underlying theory.

Imagine a scenario where you want to create an application that takes a given image of a face and changes the facial expression in a way that you want. Deep fakes come in handy in this scenario. While we will not discuss the very latest in deep fakes in this book, techniques such as few-shot adversarial learning are developed to generate realistic images with the facial expression of interest. Knowledge of how deep fakes work and GANs (which you will learn about in the next chapters) will help you identify videos that are fake videos.

In the task of deep fakery, we would have a few hundred pictures of person A and a few hundred pictures of person B. The objective is to reconstruct person B's face with the facial expression of person A and vice...

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Authors (2)

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Profile icon V Kishore Ayyadevara
LinkedIn
V Kishore Ayyadevara leads a team focused on using AI to solve problems in the healthcare space. He has 10 years' experience in data science, solving problems to improve customer experience in leading technology companies. In his current role, he is responsible for developing a variety of cutting edge analytical solutions that have an impact at scale while building strong technical teams. Prior to this, Kishore authored three books — Pro Machine Learning Algorithms, Hands-on Machine Learning with Google Cloud Platform, and SciPy Recipes. Kishore is an active learner with keen interest in identifying problems that can be solved using data, simplifying the complexity and in transferring techniques across domains to achieve quantifiable results.
Read more
See other products by V Kishore Ayyadevara
Profile icon Yeshwanth Reddy
LinkedIn
Yeshwanth is a highly accomplished data scientist manager with 9+ years of experience in deep learning and document analysis. He has made significant contributions to the field, including building software for end-to-end document digitization, resulting in substantial cost savings. Yeshwanth's expertise extends to developing modules in OCR, word detection, and synthetic document generation. His groundbreaking work has been recognized through multiple patents. He also created a few Python libraries. With a passion for disrupting unsupervised and self-supervised learning, Yeshwanth is dedicated to reducing reliance on manual annotation and driving innovative solutions in the field of data science.
Read more
See other products by Yeshwanth Reddy
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