3D Plane Detection

Description from the archive archive 2025-07-28.

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Most implemented papers archive 2025-07-28

7 shown of 7 papers with code (10 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Image
  10 Dec 2018 2 repositories listed
  This paper proposes a deep neural architecture, PlaneRCNN, that detects and reconstructs piecewise planar surfaces from a single RGB image.
• Towards In-the-wild 3D Plane Reconstruction from a Single Image
  3 Jun 2025 1 repository listed Syntology ran 3 of 9 samples · 6 unverified
  To enable data-driven models across multiple domains, we have curated a large-scale planar benchmark, comprising over 14 datasets and 560, 000 high-resolution, dense planar annotations for diverse indoor and outdoor…
• MonoPlane: Exploiting Monocular Geometric Cues for Generalizable 3D Plane Reconstruction
  2 Nov 2024 1 repository listed
  This paper presents a generalizable 3D plane detection and reconstruction framework named MonoPlane.
• PlanarRecon: Real-time 3D Plane Detection and Reconstruction from Posed Monocular Videos
  15 Jun 2022 1 repository listed Syntology ran 5 of 7 samples · 2 unverified
  We present PlanarRecon -- a novel framework for globally coherent detection and reconstruction of 3D planes from a posed monocular video.
• DeepInSAR: A Deep Learning Framework for SAR Interferometric Phase Restoration and Coherence Estimation
  6 Sep 2019 1 repository listed
  In this work, we propose a deep convolutional neural network (CNN) based model DeepInSAR to intelligently solve both the phase filtering and coherence estimation problems.
• Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding
  26 Feb 2019 1 repository listed Syntology ran 2 of 13 samples · 11 unverified
  In the first stage, we train a CNN to map each pixel to an embedding space where pixels from the same plane instance have similar embeddings.
• Latent RANSAC
  20 Feb 2018 1 repository listed
  We present a method that can evaluate a RANSAC hypothesis in constant time, i.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.