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Intro
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Classroom Contents
Learning 3D Reconstruction in Function Space - Long Version
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- 1 Intro
- 2 Traditional 3D Reconstruction Pipeline
- 3 3D Representations
- 4 Network Architecture
- 5 Training Objective
- 6 Texture Fields
- 7 Representation Power (Fit to 10 Models)
- 8 Occupancy Flow
- 9 Temporal Encoder
- 10 Loss Functions
- 11 Differentiable Volumetric Rendering
- 12 Universal Differentiable Renderer for Implicit Neural Represen
- 13 Learning Implicit Surface Light Fields
- 14 Single View Appearance Prediction
- 15 Convolutional Occupancy Networks
- 16 Deep Structured Implicit Functions
- 17 NeRF: Representing Scenes as Neural Radiance Fields
- 18 Summary
