Explore the groundbreaking concept of Neural Radiance Fields (NeRFs) in this informative video explanation. Delve into the paper "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis" and gain a comprehensive understanding of this innovative technique for 3D scene representation and view synthesis. Learn about the NeRF network architecture, key concepts, learning process, volume rendering, loss function, and advanced tricks like positional encoding and hierarchical sampling. Discover how NeRFs revolutionize the field of computer vision and graphics by enabling high-quality novel view synthesis from a sparse set of input images.
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.
