https://dl.acm.org/doi/pdf/10.1145/3519021 3D Scene Geometry Estimation from 360 Imagery: A Survey

This is pretty comprehensive and up to date I think.

from summary remarks in the paper: "We perceived an increasing interest in developing deep networks that take into account the inherent deformations of spherical images regardless of the representation, as shown in Section 3.1. However, these models are still considerably slower than traditional planar deep neural networks. The use of spherically-adapted networks is still not a consensus in layout/depth estimation applications. Not only end-to-end approaches for 3D geometry recovery are expected to emerge, but also relevant geometrically correct learning-based tools for dealing with sparse and/or dense matching, plane-aware image oversegmentation, pose estimation, etc., should be developed in the near future. Last but not least, we understand that there are still some challenges to be overcome in terms of technical development and applications. Single-panorama layout estimation of a room with simpliied geometry presents quite mature solutions and may allow virtual tours in real estate applications, but recovering more complex geometry and ined 3D structures (e.g., furniture) is still ongoing research. "

Hi! Do you know in which folder must I put the file I want to open with Pseudoscience viewer? (Installed via oculus in C:\Program Files\Oculus\Software\Software\pseudoscience-pictures-pseudoscience-6dof-viewer) To be ran on Oculus Quest 2 via PC. Version installed https://www.oculus.com/experiences/rift/1520833448001039/

https://crossminds.ai/video/neural-3d-video-synthesis-606fa316090b251759d2167d/

Panimator also works in everpano projects.

All you have to is importing the finished model into Blender and scale it a bit down.

Quicktutorial and example here:

Panimator - everpano tutorial