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  4. A Post Processing Technique to Automatically Remove Floater Artifacts in Neural Radiance Fields
 
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2023
Journal Article
Title

A Post Processing Technique to Automatically Remove Floater Artifacts in Neural Radiance Fields

Abstract
Neural Radiance Fields have revolutionized Novel View Synthesis by providing impressive levels of realism. However, in most in‐the‐wild scenes they suffer from floater artifacts that occur due to sparse input images or strong view‐dependent effects. We propose an approach that uses neighborhood based clustering and a consistency metric on NeRF models trained on different scene scales to identify regions that contain floater artifacts based on Instant‐NGPs multiscale occupancy grids. These occupancy grids contain the position of relevant optical densities in the scene. By pruning the regions that we identified as containing floater artifacts, they are omitted during the rendering process, leading to higher quality resulting images. Our approach has no negative runtime implications for the rendering process and does not require retraining of the underlying Multi Layer Perceptron. We show on a qualitative base, that our approach is suited to remove floater artifacts while preserving most of the scenes relevant geometry. Furthermore, we conduct a comparison to state‐of‐the‐art techniques on the Nerfbusters dataset, that was created with measuring the implications of floater artifacts in mind. This comparison shows, that our method outperforms currently available techniques. Our approach does not require additional user input, but can be be used in an interactive manner. In general, the presented approach is applicable to every architecture that uses an explicit representation of a scene's occupancy distribution to accelerate the rendering process.
Author(s)
Wirth, Tristan
TU Darmstadt, Fachgebiet Graphisch-Interaktive Systeme  
Rak, Arne
TU Darmstadt, Fachgebiet Graphisch-Interaktive Systeme  
Knauthe, Volker
TU Darmstadt, Fachgebiet Graphisch-Interaktive Systeme  
Fellner, Dieter
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Journal
Computer graphics forum  
Open Access
File(s)
Download (21.82 MB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.1111/cgf.14977
10.24406/publica-3217
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Branche: Information Technology

  • Research Line: Computer graphics (CG)

  • LTA: Generation, capture, processing, and output of images and 3D models

  • Volume rendering

  • Post processing

  • Machine Learning

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