Contribution to a conference proceedings/Contribution to a book PUBDB-2023-07544

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png
VRS-NeRF: Accelerating Neural Radiance Field Rendering with Variable Rate Shading

 ;  ;  ;  ;

2023
IEEE

2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) : [Proceedings] - IEEE, 2023. - ISBN 979-8-3503-2838-7 - doi:10.1109/ISMAR59233.2023.00039
2023 IEEE International Symposium on Mixed and Augmented Reality, ISMAR, SydneySydney, Australia, 16 Oct 2023 - 20 Oct 20232023-10-162023-10-20
IEEE 243 - 252 () [10.1109/ISMAR59233.2023.00039]  GO

This record in other databases:    

Please use a persistent id in citations: doi:

Abstract: Recent advancements in Neural Radiance Fields (NeRF) provide enormous potential for a wide range of Mixed Reality (MR) applications. However, the applicability of NeRF to real-time MR systems is still largely limited by the rendering performance of NeRF. In this paper, we present a novel approach for Variable Rate Shading for Neural Radiance Fields (VRS-NeRF). In contrast to previous techniques, our approach does not require training multiple neural networks or re-training of already existing ones, but instead utilizes the raytracing properties of NeRF. This is achieved by merging rays depending on a variable shading rate, which reduces the overall number of queries to the neural network. We demonstrate the generalizability of our approach by implementing three alternative functions for the determination of the shading rate. The first method uses the gaze of users to effectively implement a foveated rendering technique in NeRF. For the other two techniques, we utilize shading rates based on edges and saliency. Based on a psychophysical experiment and multiple image-based metrics, we suggest a set of parameters for each technique, yielding an optimal tradeoff between rendering performance gain and perceived visual quality.


Contributing Institute(s):
  1. Control-System (MCS)
Research Program(s):
  1. 621 - Accelerator Research and Development (POF4-621) (POF4-621)
  2. HIDSS-0002 - DASHH: Data Science in Hamburg - Helmholtz Graduate School for the Structure of Matter (2019_IVF-HIDSS-0002) (2019_IVF-HIDSS-0002)
Experiment(s):
  1. No specific instrument

Appears in the scientific report 2023
Click to display QR Code for this record

The record appears in these collections:
Private Collections > >DESY > >M > >MCS > MCS
Document types > Events > Contributions to a conference proceedings
Document types > Books > Contribution to a book
Public records
Publications database

 Record created 2023-12-05, last modified 2025-07-24


Restricted:
Download fulltext PDF Download fulltext PDF (PDFA)
Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)