This course aims to explain Neural Radiance Fields (NeRFs) and their application in representing scenes for view synthesis. The learning outcomes include understanding the goal of NeRFs, grasping the NeRF network architecture, learning how NeRFs operate, comprehending volume rendering intuition, and implementing positional encoding and hierarchical sampling tricks. The course is structured with a focus on theoretical concepts and practical techniques related to NeRFs. It is suitable for individuals interested in deep learning, computer vision, and neural network applications.
NeRFs- Neural Radiance Fields - Paper Explained
Overview
Syllabus
- Introduction
- Goal of NeRFs
- NeRF network architecture
- The key idea you need to understand
- How NeRFs learn and work
- Intuition behind volume rendering
- Loss function
- Trick #1: Positional Encoding
- Trick #2: Hierarchical sampling
- Ending
Taught by
Aladdin Persson
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Reviews
5.0 rating, based on 1 Class Central review
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Very well explained, very interesting course if you are just starting on the subject of NeRFs. The course avoids technical mathematics unless necessary. Overall great introduction to NeRFs.
