Learning 3D Reconstruction in Function Space - Long Version

Learning 3D Reconstruction in Function Space - Long Version

Andreas Geiger via YouTube Direct link

Texture Fields

6 of 18

6 of 18

Texture Fields

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Learning 3D Reconstruction in Function Space - Long Version

Automatically move to the next video in the Classroom when playback concludes

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

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.