Efficient Non-Line-of-Sight Imaging from Transient Sinograms
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Abstract (arXiv)
Non-line-of-sight (NLOS) imaging techniques use light that diffusely reflects off of visible surfaces (e.g., walls) to see around corners. One approach involves using pulsed lasers and ultrafast sensors to measure the travel time of multiply scattered light. Unlike existing NLOS techniques that generally require densely raster scanning points across the entirety of a relay wall, we explore a more efficient form of NLOS scanning that reduces both acquisition times and computational requirements. We propose a circular and confocal non-line-of-sight (C2NLOS) scan that involves illuminating and imaging a common point, and scanning this point in a circular path along a wall. We observe that (1) these C2NLOS measurements consist of a superposition of sinusoids, which we refer to as a transient sinogram, (2) there exists computationally efficient reconstruction procedures that transform these sinusoidal measurements into 3D positions of hidden scatterers or NLOS images of hidden objects, and (3) despite operating on an order of magnitude fewer measurements than previous approaches, these C2NLOS scans provide sufficient information about the hidden scene to solve these different NLOS imaging tasks. We show results from both simulated and real C2NLOS scans.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Aug 2020.
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Citing papers per year: 2021: 4; 2022: 2; 2023: 2; 2024: 2; 2025: 2.
12 papers.
- 2021Non-line-of-Sight Imaging via Neural Transient Fieldscited by 41
- 2021Recent Advances on Non-Line-of-Sight Imaging: Conventional Physical Models, Deep Learning, and New Scenescited by 10
- 2022Few-shot Non-line-of-sight Imaging with Signal-surface Collaborative Regularizationcited by 8
- 20243DFIRES: Few Image 3D REconstruction for Scenes with Hidden Surfacecited by 6
- 2024Learning to Enhance Aperture Phasor Field for Non-Line-of-Sight Imagingcited by 3
- 2023Curvature regularization for Non-line-of-sight Imaging from Under-sampled Datacited by 2
- 2021Towards Non-Line-of-Sight Photographycited by 1
- 2023Domain Reduction Strategy for Non Line of Sight Imagingcited by 1
- 2025MARMOT: Masked Autoencoder for Modeling Transient Imagingcited by 1
- 2021Onsite Non-Line-of-Sight Imaging via Online Calibrationscited by 0
- 2022Unified Simulation, Perception, and Generation of Human Behaviorcited by 0
- 2025TransiT: Transient Transformer for Non-line-of-sight Videographycited by 0
- 2025MARMOT: Masked Autoencoder for Modeling Transient Imaging10 Jun 2025
- 2025TransiT: Transient Transformer for Non-line-of-sight Videography14 Mar 2025
- 2024Learning to Enhance Aperture Phasor Field for Non-Line-of-Sight Imaging26 Jul 2024
- 20243DFIRES: Few Image 3D REconstruction for Scenes with Hidden Surface13 Mar 2024
- 2023Domain Reduction Strategy for Non Line of Sight Imaging20 Aug 2023
- 2023Curvature regularization for Non-line-of-sight Imaging from Under-sampled Data1 Jan 2023
- 2022Few-shot Non-line-of-sight Imaging with Signal-surface Collaborative Regularization21 Nov 2022
- 2022Unified Simulation, Perception, and Generation of Human Behavior28 Apr 2022
- 2021Onsite Non-Line-of-Sight Imaging via Online Calibrations29 Dec 2021
- 2021Towards Non-Line-of-Sight Photography16 Sep 2021
- 2021Recent Advances on Non-Line-of-Sight Imaging: Conventional Physical Models, Deep Learning, and New Scenes28 Apr 2021
- 2021Non-line-of-Sight Imaging via Neural Transient Fields2 Jan 2021