mlsanityData to 14 Oct 2026

Neural Radiance Field Image Refinement through End-to-End Sampling Point Optimization

arXiv 2410.14958 ↗First posted 19 Oct 2024cs.CV cs.LGcited by 0

Not on the map. Why?

Abstract (arXiv)

Neural Radiance Field (NeRF), capable of synthesizing high-quality novel viewpoint images, suffers from issues like artifact occurrence due to its fixed sampling points during rendering. This study proposes a method that optimizes sampling points to reduce artifacts and produce more detailed images.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 5 references that are in the map. First posted on arXiv 19 Oct 2024.

Builds on

4 of 5 references.

References · 4

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  2. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,964
  3. 2021MLP-Mixer: An all-MLP Architecture for Visioncited by 1,446
  4. 2022AdaNeRF: Adaptive Sampling for Real-time Rendering of Neural Radiance Fieldscited by 68

Built on by

Not cited yet.