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SynSin: End-to-end View Synthesis from a Single Image (CVPR 2020)
Authors: Olivia Wiles, Georgia Gkioxari, Richard Szeliski, Justin Johnson
Method 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 
