Détail de l'auteur
Auteur Xudong MA |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier Faire une suggestion Affiner la recherche
3D Deep Learning with Python : Design and develop your computer vision model with 3D data using PyTorch3D and more / Xudong MA / PACKT PUBLISHING (2022)
Titre : 3D Deep Learning with Python : Design and develop your computer vision model with 3D data using PyTorch3D and more Type de document : e-book Auteurs : Xudong MA Editeur : PACKT PUBLISHING Année de publication : 2022 ISBN/ISSN/EAN : 9781803247823 Note générale : copyrighted Langues : Anglais (eng) Résumé : Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with easeKey FeaturesUnderstand 3D data processing with rendering, PyTorch optimization, and heterogeneous batchingImplement differentiable rendering concepts with practical examplesDiscover how you can ease your work with the latest 3D deep learning techniques using PyTorch3DBook DescriptionWith 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.By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently.What you will learnDevelop 3D computer vision models for interacting with the environmentGet to grips with 3D data handling with point clouds, meshes, ply, and obj file formatWork with 3D geometry, camera models, and coordination and convert between themUnderstand concepts of rendering, shading, and more with easeImplement differential rendering for many 3D deep learning modelsAdvanced state-of-the-art 3D deep learning models like Nerf, synsin, mesh RCNNWho this book is forThis book is for beginner to intermediate-level machine learning practitioners, data scientists, ML engineers, and DL engineers who are looking to become well-versed with computer vision techniques using 3D data. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88937351 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=561366
LIBRARY - Campus Rouen
NEOMA Business School
pmb
-
59 Rue Taittinger, 51100 Reims
-
00 33 (0)3 26 77 46 15
Library Campus Reims
-
1 Rue du Maréchal Juin, BP 215
76825 Mont Saint Aignan cedex -
00 33 (0)2 32 82 58 26