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In computer vision and computer graphics, 4D reconstruction is the process of capturing the shape and appearance of real objects along a temporal dimension.[1][2][3][4] This process can be accomplished by methods such as depth camera imaging,[1] photometric stereo, or structure from motion,[5] and is also referred to as spatio-temporal reconstruction.[4]
Extending 3D Gaussian splatting to dynamic scenes, 3D Temporal Gaussian splatting incorporates a time component, allowing for real-time rendering of dynamic scenes with high resolutions.[6] It represents and renders dynamic scenes by modeling complex motions while maintaining efficiency. The method uses a HexPlane to connect adjacent Gaussians, providing an accurate representation of position and shape deformations. By utilizing only a single set of canonical 3D Gaussians and predictive analytics, it models how they move over different timestamps.[7]
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.[citation needed]
Achievements of this technique include real-time rendering on dynamic scenes with high resolutions, while maintaining quality. It showcases potential applications for future developments in film and other media, although there are current limitations regarding the length of motion captured.[7]
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