View source for Image-based rendering

Image-based rendering focuses on rendering scenes from existing captured or rasterized images.<br>
View synthesis focuses on rendering the scene from a new viewpoint based on the captured information.<br>
Other research focuses on adding new objects, performing relighting, stylization, and other AR effects.

==Implicit Representations==
===Light Fields===
{{ main | Light field}}
Light fields capture the accumulated radiance of light rays within the scene.<br>
Traditionally stored as a grid of images or videos.

===Light Field Networks===
This is an implicit representation similar to NeRF.<br>
However, you directly predict colors from light rays instead of performing volume rendering.

===NeRF===
{{ main | NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis }}
NeRF preprocesses unstructured light fields into a neural network (MLP) representation which predicts radiance at different points during volume rendering.

;Resources
* [https://github.com/yenchenlin/awesome-NeRF yenchenlin/awesome-NeRF]
* [https://dellaert.github.io/NeRF/ NeRF explosion 2020]

==Layered Representations==
Some notable people here are [https://scholar.google.com/citations?user=Db4BCX8AAAAJ&hl=en&oi=ao Noah Snavely] and [https://scholar.google.com/citations?user=IkpNZAoAAAAJ&hl=en&oi=sra Richard Tucker].  
Representations here vary from implicit (MPI, MSI) to explicit (LDI, Point Clouds).

===Multi-plane Image (MPI)===
Multiple perpendicular planes each with some transparency which are composited together.
* [https://arxiv.org/abs/1805.09817 Stereo Magnification (SIGGRAPH 2018)]
* [https://openaccess.thecvf.com/content_CVPR_2019/html/Flynn_DeepView_View_Synthesis_With_Learned_Gradient_Descent_CVPR_2019_paper.html DeepView (CVPR 2019)]

===Layered Depth Image (LDI)===
Multiple meshes each with some transparency. Unlike MPI, these meshes are not necessarily planes but may not correspond directly to scene objects.
* [https://facebookresearch.github.io/one_shot_3d_photography/ One-shot 3D photography]
* Casual 3D Photography

===Multi-sphere Image (MSI)===
Similar to MPI but using spheres.
* [http://visual.cs.brown.edu/projects/matryodshka-webpage/ Matryodshka (ECCV 2020)] - Renders 6-dof video from ODS videos.

===Point Clouds===
* [https://www.robots.ox.ac.uk/~ow/synsin.html SynSin]

==Classical Reconstruction==
Reconstruction aims to recreate the 3D scene from a set of input images, typically as a mesh or point cloud  
Techniques include structure from motion, multi-view stereo.  
This type of reconstruction is also studied in the field of photogrammetry.