# PoRF: Pose Residual Field for Accurate Neural Surface Reconstruction

arXiv: https://arxiv.org/abs/2310.07449 · HTML: https://mlsanity.com/paper/2310.07449/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- Builds on 30 of its 46 references that are in the map.
- First posted on arXiv 11 Oct 2023.

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

- [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](https://mlsanity.com/paper/2201.05989/) (2022)
- [Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields](https://mlsanity.com/paper/2111.12077/) (2021)
- [NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction](https://mlsanity.com/paper/2106.10689/) (2021)
- [Volume Rendering of Neural Implicit Surfaces](https://mlsanity.com/paper/2106.12052/) (2021)
- [LoFTR: Detector-Free Local Feature Matching with Transformers](https://mlsanity.com/paper/2104.00680/) (2021)
- [NeRF++: Analyzing and Improving Neural Radiance Fields](https://mlsanity.com/paper/2010.07492/) (2020)
- [MVSNet: Depth Inference for Unstructured Multi-view Stereo](https://mlsanity.com/paper/1804.02505/) (2018)
- [Open3D: A Modern Library for 3D Data Processing](https://mlsanity.com/paper/1801.09847/) (2018)
- [Implicit Geometric Regularization for Learning Shapes](https://mlsanity.com/paper/2002.10099/) (2020)
- [BARF: Bundle-Adjusting Neural Radiance Fields](https://mlsanity.com/paper/2104.06405/) (2021)
- [Nerfstudio: A Modular Framework for Neural Radiance Field Development](https://mlsanity.com/paper/2302.04264/) (2023)
- [Point-NeRF: Point-based Neural Radiance Fields](https://mlsanity.com/paper/2201.08845/) (2022)
- [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)
- [Neural RGB-D Surface Reconstruction](https://mlsanity.com/paper/2104.04532/) (2021)
- [Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inference](https://mlsanity.com/paper/1902.10556/) (2019)
- [NoPe-NeRF: Optimising Neural Radiance Field with No Pose Prior](https://mlsanity.com/paper/2212.07388/) (2022)
- [Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstruction](https://mlsanity.com/paper/2205.15848/) (2022)
- [Self-Calibrating Neural Radiance Fields](https://mlsanity.com/paper/2108.13826/) (2021)
- [SPARF: Neural Radiance Fields from Sparse and Noisy Poses](https://mlsanity.com/paper/2211.11738/) (2022)
- [Improving neural implicit surfaces geometry with patch warping](https://mlsanity.com/paper/2112.09648/) (2021)
- [NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal Priors](https://mlsanity.com/paper/2206.13597/) (2022)
- [HF-NeuS: Improved Surface Reconstruction Using High-Frequency Details](https://mlsanity.com/paper/2206.07850/) (2022)
- [Visibility-aware Multi-view Stereo Network](https://mlsanity.com/paper/2008.07928/) (2020)
- [Voxurf: Voxel-based Efficient and Accurate Neural Surface Reconstruction](https://mlsanity.com/paper/2208.12697/) (2022)
- [Local-to-Global Registration for Bundle-Adjusting Neural Radiance Fields](https://mlsanity.com/paper/2211.11505/) (2022)
- [Critical Regularizations for Neural Surface Reconstruction in the Wild](https://mlsanity.com/paper/2206.03087/) (2022)
- [SiNeRF: Sinusoidal Neural Radiance Fields for Joint Pose Estimation and Scene Reconstruction](https://mlsanity.com/paper/2210.04553/) (2022)
- [BNV-Fusion: Dense 3D Reconstruction using Bi-level Neural Volume Fusion](https://mlsanity.com/paper/2204.01139/) (2022)
- [MobileBrick: Building LEGO for 3D Reconstruction on Mobile Devices](https://mlsanity.com/paper/2303.01932/) (2023)

## Built on by (most cited first, 19 of 19)

- [Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs](https://mlsanity.com/paper/2408.13912/) (2024)
- [When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models](https://mlsanity.com/paper/2405.10255/) (2024)
- [3R-GS: Best Practice in Optimizing Camera Poses Along with 3DGS](https://mlsanity.com/paper/2504.04294/) (2025)
- [RainyScape: Unsupervised Rainy Scene Reconstruction using Decoupled Neural Rendering](https://mlsanity.com/paper/2404.11401/) (2024)
- [Sparfels: Fast Reconstruction from Sparse Unposed Imagery](https://mlsanity.com/paper/2505.02178/) (2025)
- [VGGT-X: When VGGT Meets Dense Novel View Synthesis](https://mlsanity.com/paper/2509.25191/) (2025)
- [CrossScore: Towards Multi-View Image Evaluation and Scoring](https://mlsanity.com/paper/2404.14409/) (2024)
- [SurfaceSplat: Connecting Surface Reconstruction and Gaussian Splatting](https://mlsanity.com/paper/2507.15602/) (2025)
- [Invertible Neural Warp for NeRF](https://mlsanity.com/paper/2407.12354/) (2024)
- [SG-NeRF: Neural Surface Reconstruction with Scene Graph Optimization](https://mlsanity.com/paper/2407.12667/) (2024)
- [RemixFusion: Residual-based Mixed Representation for Large-scale Online RGB-D Reconstruction](https://mlsanity.com/paper/2507.17594/) (2025)
- [LighthouseGS: Indoor Structure-aware 3D Gaussian Splatting for Panorama-Style Mobile Captures](https://mlsanity.com/paper/2507.06109/) (2025)
- [Hybrid bundle-adjusting 3D Gaussians for view consistent rendering with pose optimization](https://mlsanity.com/paper/2410.13280/) (2024)
- [Robust SG-NeRF: Robust Scene Graph Aided Neural Surface Reconstruction](https://mlsanity.com/paper/2411.13620/) (2024)
- [RA-NeRF: Robust Neural Radiance Field Reconstruction with Accurate Camera Pose Estimation under Complex Trajectories](https://mlsanity.com/paper/2506.15242/) (2025)
- [Improving Multi-View Reconstruction via Texture-Guided Gaussian-Mesh Joint Optimization](https://mlsanity.com/paper/2511.03950/) (2025)
- [GloSplat: Joint Pose-Appearance Optimization for Faster and More Accurate 3D Reconstruction](https://mlsanity.com/paper/2603.04847/) (2026)
- [Triangulation-Free Bundle Adjustment with Graduated Non-Convexity for Camera Pose Refinement from Coarse Priors](https://mlsanity.com/paper/2608.21008/) (2026)
- [OC-GS: Gaussian Splatting for Irregular Turntable Capture](https://mlsanity.com/paper/2609.31572/) (2026)

## Abstract (arXiv)

Neural surface reconstruction is sensitive to the camera pose noise, even if state-of-the-art pose estimators like COLMAP or ARKit are used. More importantly, existing Pose-NeRF joint optimisation methods have struggled to improve pose accuracy in challenging real-world scenarios. To overcome the challenges, we introduce the pose residual field (PoRF), a novel implicit representation that uses an MLP for regressing pose updates. This is more robust than the conventional pose parameter optimisation due to parameter sharing that leverages global information over the entire sequence. Furthermore, we propose an epipolar geometry loss to enhance the supervision that leverages the correspondences exported from COLMAP results without the extra computational overhead. Our method yields promising results. On the DTU dataset, we reduce the rotation error by 78% for COLMAP poses, leading to the decreased reconstruction Chamfer distance from 3.48mm to 0.85mm. On the MobileBrick dataset that contains casually captured unbounded 360-degree videos, our method refines ARKit poses and improves the reconstruction F1 score from 69.18 to 75.67, outperforming that with the dataset provided ground-truth pose (75.14). These achievements demonstrate the efficacy of our approach in refining camera poses and improving the accuracy of neural surface reconstruction in real-world scenarios.