Google patents method to smooth 3D scene rendering from photos
This filing describes a way to make 3D models built from photos look smoother and more realistic. It uses a technique called neural radiance fields, which mathematically describes how light bounces in a scene, but adds a specific sampling pattern to fix blurry or jagged edges that usually appear when zooming in.
In the filing’s own words
Provided are systems and methods for anti-aliased grid-based neural radiance fields. Neural Radiance Field (NeRF) training can be accelerated through the use of grid-based representations in the learned mapping from spatial coordinates to colors and volumetric density of the NeRF model. However, these grid-based approaches lack an explicit understanding of scale and therefore often introduce aliasing, usually in the form of jaggies or missing scene content. The present disclosure provides an improved approach for anti-aliasing a NeRF model that yields error rates that are significantly lower than prior techniques and that trains significantly faster than existing approaches.
What exactly they claim (claim 1)
1. A computing system, the system comprising: one or more processors; and one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors, cause the computing system to perform operations, the operations comprising: obtaining a view dataset comprising data descriptive of one or more two-dimensional views of a scene; parameterizing a multidimensional representation of the scene using one or more feature grids; sampling a plurality of samples along a sampling direction of the multidimensional representation according to a multisampling pattern, the multisampling pattern representing a conical frustum; generating one or more isotropic Gaussians based on the plurality of samples; interpolating the one or more isotropic Gaussians into the one or more feature grids to produce a feature set; providing the feature set as input to a proposal model; and generating, based on output of the proposal model, a novel two-dimensional view of the scene.
Facts
- Company
- Google (Google LLC)
- Official title
- Systems and Methods for Anti-Aliased Grid-Based Neural Radiance Fields
- Publication number
- US20260278918A1
- Application number
- 19168173
- Filed
- Dec 22, 2023
- Published
- Sep 17, 2026
- Inventors
- 5
- Claims
- 20
Classified under
G06T 15/20 Physics & computingMore from Google in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.