PlaneNet is an end-to-end deep learning architecture that infers plane parameters and corresponding segmentation masks from a single RGB image. The model performs geometric scene understanding by detecting and segmenting planar surfaces in 3D space. It was published at CVPR 2018 and includes both TensorFlow and experimental PyTorch implementations for training and testing.