View source for SynSin: End-to-end View Synthesis from a Single Image

SynSin: End-to-end View Synthesis from a Single Image (CVPR 2020)

Authors: Olivia Wiles, Georgia Gkioxari, Richard Szeliski, Justin Johnson  
Affiliations: University of Oxford, Facebook AI Research, Facebook, University of Michigan

* [http://www.robots.ox.ac.uk/~ow/synsin.html#:~:text=End%2Dto%2Dend%20view%20synthesis%3A%20Given%20a%20single%20RGB,to%20synthesise%20the%20output%20image. Website]
* [http://openaccess.thecvf.com/content_CVPR_2020/html/Wiles_SynSin_End-to-End_View_Synthesis_From_a_Single_Image_CVPR_2020_paper.html CVF Mirror] [https://arxiv.org/abs/1912.08804 Arxiv mirror]
* [http://openaccess.thecvf.com/content_CVPR_2020/supplemental/Wiles_SynSin_End-to-End_View_CVPR_2020_supplemental.zip Supp]

==Method==
[[File:Synsin cvpr2020 fig2.png|500px|thumb|center|Figure 2 from SynSin Paper]]

# First a depth map and a set of features are generated for each pixel using depth network \(d\) and feature network \(f\).
# The depths are used to create a 3D point cloud of features \(P\).
# Features are repositioned using the transformation matrix T.
# Repositioned features are rendered using a neural point cloud renderer.
# Rendered features are passed through a refinement network \(g\).


==Architecture==

===Feature Network===

===Depth Network===

===Neural Point Cloud Rendering===


===Refinement Network===


==Evaluation==

==References==

[[Category:Papers]]