PhD Thesis

Incorporating Uncertainty into Neural Rendering for Interpretable 3D Modeling

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Information

  • Started: 01/10/2019
  • Finished: 23/07/2024

Description

A critical limitation of current methods based on Neural Radiance Fields (NeRF) is that they are unable to quantify the uncertainty associated with the learned appearance and geometry of the scene. This information is paramount in real applications such as medical diagnosis or autonomous driving where, to reduce potentially catastrophic failures, the confidence on the model outputs must be included into the decision-making process.