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

Kazuhiro Ohta

Satoshi Ono

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.

PDF URL

Featured

Platforms

MetalSplatter Releases V1.0

The first update to MetalSplatter in a long time brings great features!

Michael Rubloff

Feb 3, 2026

Platforms

Spatial Studio for Cloud Based Gaussian Splatting

A cloud based platform for gaussian splatting and more!

Michael Rubloff

Feb 3, 2026

News

The Khronos Group Introduces a glTF Release Candidate for Gaussian Splatting

The first release candidate for glTF is here!

Michael Rubloff

Feb 3, 2026

Platforms

Splatworld's Autonomous Generation of Gaussian Splat Environments

The open platform combines a code extension, autonomous agent, and Python framework for generating and sharing Gaussian splat worlds.

Michael Rubloff

Feb 2, 2026