3D Deep Learning with Python
- Paperback: 236 pages
- Publisher: WOW! eBook (October 31, 2022)
- Language: English
- ISBN-10: 1803247827
- ISBN-13: 978-1803247823
3D Deep Learning with Python: Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with ease
With this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time.
Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You’ll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you’ll realize how coding for these deep learning models becomes easier using the PyTorch3D library.
- Develop 3D computer vision models for interacting with the environment
- Get to grips with 3D data handling with point clouds, meshes, ply, and obj file format
- Work with 3D geometry, camera models, and coordination and convert between them
- Understand concepts of rendering, shading, and more with ease
- Implement differential rendering for many 3D deep learning models
- Advanced state-of-the-art 3D deep learning models like Nerf, synsin, mesh RCNN
By the end of this 3D Deep Learning with Python book, you’ll be ready to implement your own 3D deep learning models confidently.
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