# PISR: Polarimetric Neural Implicit Surface Reconstruction for Textureless and Specular Objects

arXiv: https://arxiv.org/abs/2409.14331 · HTML: https://mlsanity.com/paper/2409.14331/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Builds on 31 of its 56 references that are in the map.
- First posted on arXiv 22 Sep 2024.

## Builds on (most cited first, 30 of 31)

- [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](https://mlsanity.com/paper/2201.05989/) (2022)
- [DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation](https://mlsanity.com/paper/1901.05103/) (2019)
- [NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction](https://mlsanity.com/paper/2106.10689/) (2021)
- [SuperGlue: Learning Feature Matching with Graph Neural Networks](https://mlsanity.com/paper/1911.11763/) (2019)
- [NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections](https://mlsanity.com/paper/2008.02268/) (2020)
- [Volume Rendering of Neural Implicit Surfaces](https://mlsanity.com/paper/2106.12052/) (2021)
- [NeRF++: Analyzing and Improving Neural Radiance Fields](https://mlsanity.com/paper/2010.07492/) (2020)
- [Implicit Geometric Regularization for Learning Shapes](https://mlsanity.com/paper/2002.10099/) (2020)
- [Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision](https://mlsanity.com/paper/1912.07372/) (2019)
- [UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction](https://mlsanity.com/paper/2104.10078/) (2021)
- [Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields](https://mlsanity.com/paper/2112.03907/) (2021)
- [MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstruction](https://mlsanity.com/paper/2206.00665/) (2022)
- [Neuralangelo: High-Fidelity Neural Surface Reconstruction](https://mlsanity.com/paper/2306.03092/) (2023)
- [PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting](https://mlsanity.com/paper/2104.00674/) (2021)
- [NeuS2: Fast Learning of Neural Implicit Surfaces for Multi-view Reconstruction](https://mlsanity.com/paper/2212.05231/) (2022)
- [Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM](https://mlsanity.com/paper/2304.14377/) (2023)
- [SparseNeuS: Fast Generalizable Neural Surface Reconstruction from Sparse Views](https://mlsanity.com/paper/2206.05737/) (2022)
- [NeRO: Neural Geometry and BRDF Reconstruction of Reflective Objects from Multiview Images](https://mlsanity.com/paper/2305.17398/) (2023)
- [Multi-Scale Geometric Consistency Guided Multi-View Stereo](https://mlsanity.com/paper/1904.08103/) (2019)
- [Ref-NeuS: Ambiguity-Reduced Neural Implicit Surface Learning for Multi-View Reconstruction with Reflection](https://mlsanity.com/paper/2303.10840/) (2023)
- [Shape from Polarization for Complex Scenes in the Wild](https://mlsanity.com/paper/2112.11377/) (2021)
- [PANDORA: Polarization-Aided Neural Decomposition Of Radiance](https://mlsanity.com/paper/2203.13458/) (2022)
- [UniSDF: Unifying Neural Representations for High-Fidelity 3D Reconstruction of Complex Scenes with Reflections](https://mlsanity.com/paper/2312.13285/) (2023)
- [Polarimetric Multi-View Inverse Rendering](https://mlsanity.com/paper/2007.08830/) (2020)
- [S3IM: Stochastic Structural SIMilarity and Its Unreasonable Effectiveness for Neural Fields](https://mlsanity.com/paper/2308.07032/) (2023)
- [NeISF: Neural Incident Stokes Field for Geometry and Material Estimation](https://mlsanity.com/paper/2311.13187/) (2023)
- [Transparent Shape from a Single View Polarization Image](https://mlsanity.com/paper/2204.06331/) (2022)
- [Perspective Phase Angle Model for Polarimetric 3D Reconstruction](https://mlsanity.com/paper/2207.09629/) (2022)
- [Polarimetric Monocular Dense Mapping Using Relative Deep Depth Prior](https://mlsanity.com/paper/2102.05212/) (2021)
- [Fresnel Microfacet BRDF: Unification of Polari-Radiometric Surface-Body Reflection](https://mlsanity.com/paper/2212.04483/) (2022)

## Built on by (most cited first, 15 of 15)

- [EnvGS: Modeling View-Dependent Appearance with Environment Gaussian](https://mlsanity.com/paper/2412.15215/) (2024)
- [NeISF++: Neural Incident Stokes Field for Polarized Inverse Rendering of Conductors and Dielectrics](https://mlsanity.com/paper/2411.10189/) (2024)
- [PolGS: Polarimetric Gaussian Splatting for Fast Reflective Surface Reconstruction](https://mlsanity.com/paper/2509.19726/) (2025)
- [PolarAnything: Diffusion-based Polarimetric Image Synthesis](https://mlsanity.com/paper/2507.17268/) (2025)
- [Glossy Object Reconstruction with Cost-effective Polarized Acquisition](https://mlsanity.com/paper/2504.07025/) (2025)
- [PMNI: Pose-free Multi-view Normal Integration for Reflective and Textureless Surface Reconstruction](https://mlsanity.com/paper/2504.08410/) (2025)
- [PolarGS: Polarimetric Cues for Ambiguity-Free Gaussian Splatting with Accurate Geometry Recovery](https://mlsanity.com/paper/2512.00794/) (2025)
- [PolarVLM: Bridging the Semantic-Physical Gap in Vision-Language Models](https://mlsanity.com/paper/2605.07574/) (2026)
- [PolarGuide-GSDR: 3D Gaussian Splatting Driven by Polarization Priors and Deferred Reflection for Real-World Reflective Scenes](https://mlsanity.com/paper/2512.02664/) (2025)
- [TraceFlow: Dynamic 3D Reconstruction of Specular Scenes Driven by Ray Tracing](https://mlsanity.com/paper/2512.10095/) (2025)
- [EvalMVX: A Unified Benchmarking for Neural 3D Reconstruction under Diverse Multiview Setups](https://mlsanity.com/paper/2602.24065/) (2026)
- [Revisiting Shape from Polarization in the Era of Vision Foundation Models](https://mlsanity.com/paper/2603.04817/) (2026)
- [PolGS++: Physically-Guided Polarimetric Gaussian Splatting for Fast Reflective Surface Reconstruction](https://mlsanity.com/paper/2603.10801/) (2026)
- [Poppy: Polarization-based Plug-and-Play Guidance for Enhancing Monocular Normal Estimation](https://mlsanity.com/paper/2603.27891/) (2026)
- [Snapshot Polarimetric Display Inverse Rendering](https://mlsanity.com/paper/2605.24915/) (2026)

## Abstract (arXiv)

Neural implicit surface reconstruction has achieved remarkable progress recently. Despite resorting to complex radiance modeling, state-of-the-art methods still struggle with textureless and specular surfaces. Different from RGB images, polarization images can provide direct constraints on the azimuth angles of the surface normals. In this paper, we present PISR, a novel method that utilizes a geometrically accurate polarimetric loss to refine shape independently of appearance. In addition, PISR smooths surface normals in image space to eliminate severe shape distortions and leverages the hash-grid-based neural signed distance function to accelerate the reconstruction. Experimental results demonstrate that PISR achieves higher accuracy and robustness, with an L1 Chamfer distance of 0.5 mm and an F-score of 99.5% at 1 mm, while converging 4~30 times faster than previous polarimetric surface reconstruction methods.