8 posts found
A beginner-friendly tour of Bayesian 3D reconstruction: why an ordinary 3D scan gives one confident answer everywhere, how turning geometry into a distribution produces honest confidence maps, and where the 'prior' that fills in unseen regions comes from.
3D Gaussian Splatting gives us a single best-fit scene — but no sense of where that geometry is trustworthy. This week we turn point-estimate splats into distributions over geometry, connecting Bayesian rendering, Fisher information, and diffusion priors back to last week's GP framework.
Highlights of AI News for April 13 - 19 2026
A step-by-step introduction to 4D Gaussian Splatting — how adding a time dimension to 3DGS enables real-time dynamic scene rendering, from deformation fields to temporal regularization.
How 4D Gaussian Splatting extends real-time radiance fields into the time domain — deformation fields, temporal regularization, neural scene flow, and the path to dynamic world models.
Map the modern image-to-3D ecosystem—from LRM-style direct regression and multi-view diffusion to latent 3D generation—and see how the frontier is now moving from static 3D to dynamic 4D worlds.
Understand 3D Gaussian Splatting from first principles—the real-time rendering technique powering next-generation world models like Marble.
Trend tutorial on World Models -- focusing on Worldlabs' Marble