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Gaussian splatting model of a collapsed building taken from drone footage. 3D Gaussian splatting is a technique used in the field of real-time radiance field rendering. [3] It enables the creation of high-quality real-time novel-view scenes by combining multiple photos or videos, addressing a significant challenge in the field.
It is sometimes referred to as "4D Gaussian splatting"; however, this naming convention implies the use of 4D Gaussian primitives (parameterized by a 4×4 mean and a 4×4 covariance matrix). Most work in this area still employs 3D Gaussian primitives, applying temporal constraints as an extra parameter of optimization.
Types of presentations of CT scans, with two examples of volume rendering. Volume rendering is distinguished from thin slice tomography presentations, and is also generally distinguished from projections of 3D models, including maximum intensity projection. [1]
Gaussian splatting is a newer method that can outperform NeRF in render time and fidelity. Rather than representing the scene as a volumetric function, it uses a sparse cloud of 3D gaussians . First, a point cloud is generated (through structure from motion ) and converted to gaussians of initial covariance, color, and opacity.
In computer graphics, view synthesis, or novel view synthesis, is a task which consists of generating images of a specific subject or scene from a specific point of view, when the only available information is pictures taken from different points of view.
It is somewhat implied that in most cases, Gaussian Splatting is three dimensional. Even if that's not the case, the subcases can be covered on the general page – Kjerish ( talk ) 05:16, 26 October 2024 (UTC) [ reply ]
Volumetric capture or volumetric video is a technique that captures a three-dimensional space, such as a location or performance. [1] This type of volumography acquires data that can be viewed on flat screens as well as using 3D displays and VR headset.
Digital photograph restoration and colorization using artificial intelligence. Image restoration is the operation of taking a corrupt/noisy image and estimating the clean, original image.