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Jianxiong Shen

3 accepted papers

2024

Estimating 3D Uncertainty Field: Quantifying Uncertainty for Neural Radiance Fields

ICRA 2024poster

Current methods based on Neural Radiance Fields (NeRF) significantly lack the capacity to quantify uncertainty in their predictions, particularly on the unseen space including the occluded and outside scene content. This limitation hinders their extensive applications in robotics, where the reliabil…

Cited by 11SourceScholar
2022

Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantification

ECCV 2022poster

"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 wh…