mlsanityData to 7 Oct 2026

Full 3D Reconstruction of Transparent Objects

arXiv 1805.03482 ↗First posted 9 May 2018cs.GR cs.CVcited by 24

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Abstract (arXiv)

Numerous techniques have been proposed for reconstructing 3D models for opaque objects in past decades. However, none of them can be directly applied to transparent objects. This paper presents a fully automatic approach for reconstructing complete 3D shapes of transparent objects. Through positioning an object on a turntable, its silhouettes and light refraction paths under different viewing directions are captured. Then, starting from an initial rough model generated from space carving, our algorithm progressively optimizes the model under three constraints: surface and refraction normal consistency, surface projection and silhouette consistency, and surface smoothness. Experimental results on both synthetic and real objects demonstrate that our method can successfully recover the complex shapes of transparent objects and faithfully reproduce their light refraction properties.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 May 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 5; 2023: 10; 2024: 2; 2025: 4; 2026: 1.

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  1. 2023BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objectscited by 70
  2. 2021RGB-D Local Implicit Function for Depth Completion of Transparent Objectscited by 64
  3. 2024BOP Challenge 2023 on Detection, Segmentation and Pose Estimation of Seen and Unseen Rigid Objectscited by 60
  4. 2022Eikonal Fields for Refractive Novel-View Synthesiscited by 30
  5. 2022Transparent Shape from a Single View Polarization Imagecited by 16
  6. 2023NeRRF: 3D Reconstruction and View Synthesis for Transparent and Specular Objects with Neural Refractive-Reflective Fieldscited by 16
  7. 2025TransparentGS: Fast Inverse Rendering of Transparent Objects with Gaussianscited by 16
  8. 2022Hybrid Mesh-neural Representation for 3D Transparent Object Reconstructioncited by 15
  9. 2023NEMTO: Neural Environment Matting for Novel View and Relighting Synthesis of Transparent Objectscited by 14
  10. 2022TODE-Trans: Transparent Object Depth Estimation with Transformercited by 13
  11. 2023Seeing Through the Glass: Neural 3D Reconstruction of Object Inside a Transparent Containercited by 10
  12. 2023NeTO:Neural Reconstruction of Transparent Objects with Self-Occlusion Aware Refraction-Tracingcited by 9
12 more
  1. 2022Polarimetric Inverse Rendering for Transparent Shapes Reconstructioncited by 8
  2. 2023RFTrans: Leveraging Refractive Flow of Transparent Objects for Surface Normal Estimation and Manipulationcited by 6
  3. 2023Towards Monocular Shape from Refractioncited by 3
  4. 2025Glossy Object Reconstruction with Cost-effective Polarized Acquisitioncited by 3
  5. 2023REF2-NeRF: Reflection and Refraction aware Neural Radiance Fieldcited by 2
  6. 2024From Transparent to Opaque: Rethinking Neural Implicit Surfaces with α-NeuScited by 2
  7. 2021Shape and Reflectance Reconstruction in Uncontrolled Environments by Differentiable Renderingcited by 1
  8. 2025RefRef: A Dataset and Benchmark for Reconstructing Refractive and Reflective Objectscited by 1
  9. 2023NERFBK: A High-Quality Benchmark for NERF-Based 3D Reconstructioncited by 0
  10. 2023Tabletop Transparent Scene Reconstruction via Epipolar-Guided Optical Flow with Monocular Depth Completion Priorcited by 0
  11. 2025HTMNet: A Hybrid Network with Transformer-Mamba Bottleneck Multimodal Fusion for Transparent and Reflective Objects Depth Completioncited by 0
  12. 2026DiffTrans: Differentiable Geometry-Materials Decomposition for Reconstructing Transparent Objectscited by 0