PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image

Understand

This paper proposes a deep neural network (DNN) for piece-wise planar depthmap reconstruction from a single RGB image.

• While DNNs have brought remarkable progress to single-image depth prediction, piece-wise planar depthmap reconstruction requires a structured geometry representation, and has been a difficult task to master even for DNNs.
• The proposed end-to-end DNN learns to directly infer a set of plane parameters and corresponding plane segmentation masks from a single RGB image.
• We have generated more than 50,000 piece-wise planar depthmaps for training and testing from ScanNet, a large-scale RGBD video database.