mlsanityData to 14 Oct 2026

Reconstructing Small 3D Objects in front of a Textured Background

arXiv 2105.11352 ↗First posted 24 May 2021cs.CVcited by 0

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Abstract (arXiv)

We present a technique for a complete 3D reconstruction of small objects moving in front of a textured background. It is a particular variation of multibody structure from motion, which specializes to two objects only. The scene is captured in several static configurations between which the relative pose of the two objects may change. We reconstruct every static configuration individually and segment the points locally by finding multiple poses of cameras that capture the scene's other configurations. Then, the local segmentation results are combined, and the reconstructions are merged into the resulting model of the scene. In experiments with real artifacts, we show that our approach has practical advantages when reconstructing 3D objects from all sides. In this setting, our method outperforms the state-of-the-art. We integrate our method into the state of the art 3D reconstruction pipeline COLMAP.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 75 references that are in the map. First posted on arXiv 24 May 2021.

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9 of 75 references.

References · 9

  1. 2019D2-Net: A Trainable CNN for Joint Detection and Description of Local Featurescited by 326
  2. 2018Neighbourhood Consensus Networkscited by 174
  3. 2017Monocular Dense 3D Reconstruction of a Complex Dynamic Scene from Two Perspective Framescited by 27
  4. 2017Multi-Class Model Fitting by Energy Minimization and Mode-Seekingcited by 19
  5. 2016Multi-body Non-rigid Structure-from-Motioncited by 14
  6. 2018Motion Segmentation by Exploiting Complementary Geometric Modelscited by 9
  7. 2015Shape Interaction Matrix Revisited and Robustified: Efficient Subspace Clustering with Corrupted and Incomplete Datacited by 8
  8. 2020A Photogrammetry-based Framework to Facilitate Image-based Modeling and Automatic Camera Trackingcited by 4
  9. 2019Robust Motion Segmentation from Pairwise Matchescited by 3

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