title: Unposed Sparse Views Room Layout Reconstruction in the Age of Pretrain
    Model
summary: Room layout estimation from multiple-perspective images is poorly
  investigated due to the complexities that emerge from multi-view geometry,
  which requires muti-step solutions such as camera intrinsic and extrinsic
  estimation, image matching, and triangulation. However, in 3D reconstruction,
  the advancement of recent 3D foundation models such as DUSt3R has shifted the
  paradigm from the traditional multi-step structure-from-motion process to an
  end-to-end single-step approach. To this end, we introduce Plane-DUSt3R, a
  novel method for multi-view room layout estimation leveraging the 3D foundation
  model DUSt3R. Plane-DUSt3R incorporates the DUSt3R framework and fine-tunes on
  a room layout dataset (Structure3D) with a modified objective to estimate
  structural planes. By generating uniform and parsimonious results, Plane-DUSt3R
  enables room layout estimation with only a single post-processing step and 2D
  detection results. Unlike previous methods that rely on single-perspective or
  panorama image, Plane-DUSt3R extends the setting to handle multiple-perspective
  images. Moreover, it offers a streamlined, end-to-end solution that simplifies
  the process and reduces error accumulation. Experimental results demonstrate
  that Plane-DUSt3R not only outperforms state-of-the-art methods on the
  synthetic dataset but also proves robust and effective on in the wild data with
  different image styles such as cartoon.Our code is available at:
  https://github.com/justacar/Plane-DUSt3R
paper_authors._id: 67c65c06e116e361574405e9
paper_authors.name: Yaxuan Huang
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-03-04T08:51:27.582Z
paper_authors._id: 642bdfc65edcc5760cb1ea12
paper_authors.avatarUrl: /avatars/599b0bbb379b43cd39097c204c946075.svg
paper_authors.fullname: huang
paper_authors.type: user
paper_authors.user: yxuan
paper_authors._id: 67c65c06e116e361574405ea
paper_authors.name: Xili Dai
paper_authors._id: 67c65c06e116e361574405eb
paper_authors.name: Jianan Wang
paper_authors._id: 67c65c06e116e361574405ec
paper_authors.name: Xianbiao Qi
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-03-04T11:01:12.106Z
paper_authors._id: 6494483aa13255720397287a
paper_authors.avatarUrl: /avatars/61ff2e0371df513194246cf6fbb2b78a.svg
paper_authors.fullname: Xianbiao Qi
paper_authors.type: user
paper_authors.user: qixianbiao
paper_authors._id: 67c65c06e116e361574405ed
paper_authors.name: Yixing Yuan
paper_authors._id: 67c65c06e116e361574405ee
paper_authors.name: Xiangyu Yue
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-03-04T11:00:56.439Z
paper_authors._id: 666a8f24e2990b0cb16b7bf9
paper_authors.avatarUrl: /avatars/fcbaf8f1e3e53a2a4a819b7cb2c53aa4.svg
paper_authors.fullname: Xiangyu Yue
paper_authors.type: user
paper_authors.user: xyyue
paper_title: Unposed Sparse Views Room Layout Reconstruction in the Age of Pretrain
    Model
paper_summary: Room layout estimation from multiple-perspective images is poorly
  investigated due to the complexities that emerge from multi-view geometry,
  which requires muti-step solutions such as camera intrinsic and extrinsic
  estimation, image matching, and triangulation. However, in 3D reconstruction,
  the advancement of recent 3D foundation models such as DUSt3R has shifted the
  paradigm from the traditional multi-step structure-from-motion process to an
  end-to-end single-step approach. To this end, we introduce Plane-DUSt3R, a
  novel method for multi-view room layout estimation leveraging the 3D foundation
  model DUSt3R. Plane-DUSt3R incorporates the DUSt3R framework and fine-tunes on
  a room layout dataset (Structure3D) with a modified objective to estimate
  structural planes. By generating uniform and parsimonious results, Plane-DUSt3R
  enables room layout estimation with only a single post-processing step and 2D
  detection results. Unlike previous methods that rely on single-perspective or
  panorama image, Plane-DUSt3R extends the setting to handle multiple-perspective
  images. Moreover, it offers a streamlined, end-to-end solution that simplifies
  the process and reduces error accumulation. Experimental results demonstrate
  that Plane-DUSt3R not only outperforms state-of-the-art methods on the
  synthetic dataset but also proves robust and effective on in the wild data with
  different image styles such as cartoon.Our code is available at:
  https://github.com/justacar/Plane-DUSt3R
paper_ai_summary: Plane-DUSt3R leverages a 3D foundation model to estimate room layouts from multiple-perspective images, offering a single-step, end-to-end solution that outperforms existing methods.
paper_ai_keywords: 3D foundation models DUSt3R multi-view geometry room layout estimation multi-step structure-from-motion camera intrinsic and extrinsic estimation image matching triangulation end-to-end approach structural planes uniform and parsimonious results single post-processing step 2D detection results multiple-perspective images in-the-wild data