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Shoot-Bounce-3D: Single-Shot Occlusion-Aware 3D from Lidar by Decomposing Two-Bounce Light

  • Tzofi Klinghoffer
  • , Siddharth Somasundaram
  • , Xiaoyu Xiang
  • , Yuchen Fan
  • , Christian Richardt
  • , Akshat Dave
  • , Ramesh Raskar
  • , Rakesh Ranjan
  • Massachusetts Institute of Technology
  • Meta
  • Meta

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

3D scene reconstruction from a single measurement is challenging, especially in the presence of occluded regions and specular materials, such as mirrors. We address these challenges by leveraging single-photon lidars. These lidars estimate depth from light that is emitted into the scene and reflected directly back to the sensor. However, they can also measure light that bounces multiple times in the scene before reaching the sensor. This multi-bounce light contains additional information that can be used to recover dense depth, occluded geometry, and material properties. Prior work with single-photon lidar, however, has only demonstrated these use cases when a laser sequentially illuminates one scene point at a time. We instead focus on the more practical - and challenging - scenario of illuminating multiple scene points simultaneously. The complexity of light transport due to the combined effects of multiplexed illumination, two-bounce light, shadows, and specular reflections is challenging to invert analytically. Instead, we propose a data-driven method to invert light transport in single-photon lidar. To enable this approach, we create the first large-scale simulated dataset of ∼100k lidar transients for indoor scenes. We use this dataset to learn a prior on complex light transport, enabling measured two-bounce light to be decomposed into the constituent contributions from each laser spot. Finally, we experimentally demonstrate how this decomposed light can be used to infer 3D geometry in scenes with occlusions and mirrors from a single measurement. Our code and dataset are released on our project webpage.

Original languageEnglish
Title of host publicationProceedings - SIGGRAPH Asia 2025 Conference Papers, SA 2025
EditorsStephen N. Spencer, Taku Komura, Michael Wimmer, Hongbo Fu
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9798400721373
DOIs
StatePublished - Dec 14 2025
Event2025 SIGGRAPH Asia 2025 Conference Papers, SA 2025 - Hong Kong, Hong Kong
Duration: Dec 15 2025Dec 18 2025

Publication series

NameProceedings - SIGGRAPH Asia 2025 Conference Papers, SA 2025

Conference

Conference2025 SIGGRAPH Asia 2025 Conference Papers, SA 2025
Country/TerritoryHong Kong
CityHong Kong
Period12/15/2512/18/25

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