PlanarRecon: Realtime 3D Plane Detection and Reconstruction from Posed Monocular Videos

作者：Yiming Xie, Matheus Gadelha, Fengting Yang, Xiaowei Zhou, Huaizu Jiang · 发表于：2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · 年份：2022 · DOI：10.1109/cvpr52688.2022.00612 · 被引用次数：34 · 研究领域：Image and Object Detection Techniques、3D Surveying and Cultural Heritage、Advanced Neural Network Applications

We present PlanarRecon - a novel framework for globally coherent detection and reconstruction of 3D planes from a posed monocular video. Unlike previous works that detect planes in 2D from a single image, PlanarRecon incrementally detects planes in 3D for each video fragment, which consists of a set of key frames, from a volumetric representation of the scene using neural networks. A learning-based tracking and fusion module is designed to merge planes from previous fragments to form a coherent global plane reconstruction. Such design allows Planar-Recon to integrate observations from multiple views within each fragment and temporal information across different ones, resulting in an accurate and coherent reconstruction of the scene abstraction with low-polygonal geometry. Experiments show that the proposed approach achieves state-of-the-art performances on the ScanNet dataset while being real-time. Code is available at the project page: https://neu-vi.github.io/planarrecon/.