Learning Pairwise Inter-Plane Relations for Piecewise Planar Reconstruction
This paper proposes a novel single-image piecewise planar reconstruction technique that infers and enforces inter-plane relationships. Our approach takes a planar reconstruction result from an existing system, then utilizes convolutional neural network (CNN) to (1) classify if two planes are orthogonal or parallel; and 2) infer if two planes are touching and, if so, where in the image. We formulate an optimization problem to refine plane parameters and employ a message passing neural network to refine plane segmentation masks by enforcing the inter-plane relations. Our qualitative and quantitative evaluations demonstrate the effectiveness of the proposed approach in terms of plane parameters and segmentation accuracy.
PDF AbstractCode
Tasks
ScanNet
LabelMe
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here
