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3D Deep Learning with Python

You're reading from   3D Deep Learning with Python Design and develop your computer vision model with 3D data using PyTorch3D and more

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Product type Paperback
Published in Oct 2022
Publisher Packt
ISBN-13 9781803247823
Length 236 pages
Edition 1st Edition
Languages
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Authors (4):
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Xudong Ma Xudong Ma
Author Profile Icon Xudong Ma
Xudong Ma
Vishakh Hegde Vishakh Hegde
Author Profile Icon Vishakh Hegde
Vishakh Hegde
Lilit Yolyan Lilit Yolyan
Author Profile Icon Lilit Yolyan
Lilit Yolyan
David Farrugia David Farrugia
Author Profile Icon David Farrugia
David Farrugia
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Toc

Table of Contents (16) Chapters Close

Preface 1. PART 1: 3D Data Processing Basics
2. Chapter 1: Introducing 3D Data Processing FREE CHAPTER 3. Chapter 2: Introducing 3D Computer Vision and Geometry 4. PART 2: 3D Deep Learning Using PyTorch3D
5. Chapter 3: Fitting Deformable Mesh Models to Raw Point Clouds 6. Chapter 4: Learning Object Pose Detection and Tracking by Differentiable Rendering 7. Chapter 5: Understanding Differentiable Volumetric Rendering 8. Chapter 6: Exploring Neural Radiance Fields (NeRF) 9. PART 3: State-of-the-art 3D Deep Learning Using PyTorch3D
10. Chapter 7: Exploring Controllable Neural Feature Fields 11. Chapter 8: Modeling the Human Body in 3D 12. Chapter 9: Performing End-to-End View Synthesis with SynSin 13. Chapter 10: Mesh R-CNN 14. Index 15. Other Books You May Enjoy

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “ Next, we need to update the ./options/options.py file”

A block of code is set as follows:

elif opt.dataset == 'kitti':
   opt.min_z = 1.0
   opt.max_z = 50.0
   opt.train_data_path = (
       './DATA/dataset_kitti/'
   )
   from data.kitti import KITTIDataLoader
   return KITTIDataLoader

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

wget https://dl.fbaipublicfiles.com/synsin/checkpoints/realestate/synsin.pth

Any command-line input or output is written as follows:

bash ./download_models.sh

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “The refinement module (g) gets inputs from the neural point cloud renderer and then outputs the final reconstructed image.”

Tips or important notes

Appear like this.

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