Thermal Polarimetric Multi-view Stereo
Not on the map. Why?
Abstract (arXiv)
This paper introduces a novel method for detailed 3D shape reconstruction utilizing thermal polarization cues. Unlike state-of-the-art methods, the proposed approach is independent of illumination and material properties. In this paper, we formulate a general theory of polarization observation and show that long-wave infrared (LWIR) polarimetric imaging is free from the ambiguities that affect visible polarization analyses. Subsequently, we propose a method for recovering detailed 3D shapes using multi-view thermal polarimetric images. Experimental results demonstrate that our approach effectively reconstructs fine details in transparent, translucent, and heterogeneous objects, outperforming existing techniques.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 55 references that are in the map. First posted on arXiv 23 Oct 2025.
Builds on
14 of 55 references.
References · 14
- 2024SAM 2: Segment Anything in Images and Videoscited by 2,784
- 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
- 2020Implicit Geometric Regularization for Learning Shapescited by 707
- 2021Shape from Polarization for Complex Scenes in the Wildcited by 53
- 2020Polarimetric Multi-View Inverse Renderingcited by 28
- 2023NeISF: Neural Incident Stokes Field for Geometry and Material Estimationcited by 25
- 2024NeRSP: Neural 3D Reconstruction for Reflective Objects with Sparse Polarized Imagescited by 22
- 2024Thermal-NeRF: Neural Radiance Fields from an Infrared Cameracited by 21
- 2023Multi-View Azimuth Stereo via Tangent Space Consistencycited by 16
- 2024Thermal3D-GS: Physics-induced 3D Gaussians for Thermal Infrared Novel-view Synthesiscited by 16
- 2024ThermalNeRF: Thermal Radiance Fieldscited by 13
- 2023Absorption-Based, Passive Range Imaging from Hyperspectral Thermal Measurementscited by 8
Built on by
Citing papers per year: 2026: 1.
1 paper.