Hands-on 3D data processing with PyTorch3D for real-world applications
Step-by-step explanations of essential concepts and practical examples
Implementation of advanced 3D deep learning algorithms such as differential rendering, NeRF, and Mesh-RCNN
Supports working with multiple 3D data formats including PLY and OBJ
Covers camera models, rendering, and geometry coordination for computer vision projects
Summarized by Shop
Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with ease
Key Features:
Understand 3D data processing with rendering, PyTorch optimization, and heterogeneous batching
Implement differentiable rendering concepts with practical examples