mlsanityData to 14 Oct 2026

NLOS-NeuS: Non-line-of-sight Neural Implicit Surface

arXiv 2303.12280 ↗First posted 22 Mar 2023cs.CV eess.IVcited by 13

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Abstract (arXiv)

Non-line-of-sight (NLOS) imaging is conducted to infer invisible scenes from indirect light on visible objects. The neural transient field (NeTF) was proposed for representing scenes as neural radiance fields in NLOS scenes. We propose NLOS neural implicit surface (NLOS-NeuS), which extends the NeTF to neural implicit surfaces with a signed distance function (SDF) for reconstructing three-dimensional surfaces in NLOS scenes. We introduce two constraints as loss functions for correctly learning an SDF to avoid non-zero level-set surfaces. We also introduce a lower bound constraint of an SDF based on the geometry of the first-returning photons. The experimental results indicate that these constraints are essential for learning a correct SDF in NLOS scenes. Compared with previous methods with discretized representation, NLOS-NeuS with the neural continuous representation enables us to reconstruct smooth surfaces while preserving fine details in NLOS scenes. To the best of our knowledge, this is the first study on neural implicit surfaces with volume rendering in NLOS scenes.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 28 of its 63 references that are in the map. First posted on arXiv 22 Mar 2023.

Builds on

28 of 63 references.

References · 28

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  3. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,041
  4. 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,712
  5. 2021Volume Rendering of Neural Implicit Surfacescited by 996
  6. 2020Convolutional Occupancy Networkscited by 761
  7. 2020Implicit Geometric Regularization for Learning Shapescited by 710
  8. 2019Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervisioncited by 700
  9. 2021UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstructioncited by 646
  10. 2019SAL: Sign Agnostic Learning of Shapes from Raw Datacited by 390
  11. 2020Implicit Functions in Feature Space for 3D Shape Reconstruction and Completioncited by 343
  12. 2020Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstructioncited by 321
16 more
  1. 2021Neural RGB-D Surface Reconstructioncited by 313
  2. 2021StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generationcited by 289
  3. 2020Neural Unsigned Distance Fields for Implicit Function Learningcited by 265
  4. 2022Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstructioncited by 212
  5. 2020Deep Reflectance Volumes: Relightable Reconstructions from Multi-View Photometric Imagescited by 98
  6. 2020SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Imagescited by 68
  7. 2022Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priorscited by 60
  8. 2021Neural Fields as Learnable Kernels for 3D Reconstructioncited by 58
  9. 2018Virtual Wave Optics for Non-Line-of-Sight Imagingcited by 54
  10. 2021Non-line-of-Sight Imaging via Neural Transient Fieldscited by 41
  11. 2020Optical Non-Line-of-Sight Physics-based 3D Human Pose Estimationcited by 34
  12. 2017Fast Back-Projection for Non-Line of Sight Reconstructioncited by 24
  13. 2018Non-Line-of-Sight Reconstruction using Efficient Transient Renderingcited by 17
  14. 2022Physics to the Rescue: Deep Non-line-of-sight Reconstruction for High-speed Imagingcited by 15
  15. 2016Recent Advances in Transient Imaging: A Computer Graphics and Vision Perspectivecited by 12
  16. 2017Neural network identification of people hidden from view with a single-pixel, single-photon detectorcited by 9

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 4; 2024: 3; 2025: 3; 2026: 3.

13 papers.

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  1. 2024Towards 3D Vision with Low-Cost Single-Photon Camerascited by 15
  2. 2024Blurred LiDAR for Sharper 3D: Robust Handheld 3D Scanning with Diffuse LiDAR and RGBcited by 10
  3. 2023PlatoNeRF: 3D Reconstruction in Plato's Cave via Single-View Two-Bounce Lidarcited by 9
  4. 2024Transientangelo: Few-Viewpoint Surface Reconstruction Using Single-Photon Lidarcited by 6
  5. 2023Seeing the World through Your Eyescited by 5
  6. 2023Omni-Line-of-Sight Imaging for Holistic Shape Reconstructioncited by 3
  7. 2023Self-Calibrating, Fully Differentiable NLOS Inverse Renderingcited by 3
  8. 2025MARMOT: Masked Autoencoder for Modeling Transient Imagingcited by 1
  9. 2025Dual-branch Graph Feature Learning for NLOS Imagingcited by 0
  10. 2025Geometric Constrained Non-Line-of-Sight Imagingcited by 0
  11. 2026DENALI: A Dataset Enabling Non-Line-of-Sight Spatial Reasoning with Low-Cost LiDARscited by 0
  12. 2026Imaging Hidden Objects with Consumer LiDAR via Motion Induced Samplingcited by 0
1 more
  1. 2026Non-line-of-sight imaging with arbitrary relay surface geometries via 3D Gaussian Transient Renderingcited by 0