Seeing Around Corners in Real-Time using Mobile LiDAR

Non-line-of-sight imaging extends perception beyond direct view but has remained impractical on everyday devices. This demo presents a real-time system that uses a commercial mobile LiDAR sensor to track and reconstruct objects hidden around corners. By aggregating multi-bounce LiDAR returns across consecutive frames, our method boosts signal-to-noise ratio and emulates longer exposures, enabling motion-compensated tracking and reconstruction at ~15 Hz. Our system validates the practical implementation of non-line-of-sight imaging on consumer hardware, paving the way for next-generation applications in robotics, autonomous navigation, and augmented reality.

Aaron Young, Siddharth Somasundaram, Nick Tsao, Nikhil Behari, Akshat Dave, Adithya Pediredla, Ramesh Raskar

Project Papers

Enhancing Autonomous Navigation by Imaging Hidden Objects using Single-Photon LiDAR Aaron Young^*, Nevindu M. Batagoda^*, Harry Zhang, Akshat Dave, Adithya Pediredla, Dan Negrut, Ramesh Raskar

Paper | Code | Video

Citation

If you would like to cite this demo, please use the following BibTeX entry:

@inproceedings{young2024enhancing,
    author = {Young, Aaron and Batagoda, Nevindu M. and Zhang, Harry and Dave, Akshat and Pediredla, Adithya and Negrut, Dan and Raskar, Ramesh},
    title = {Enhancing Autonomous Navigation by Imaging Hidden Objects using Single-Photon LiDAR},
    booktitle = {ArXiv},
    year = {2024}
}

@software{young2025seeing,
    author = {Aaron Young and Siddharth Somasundaram and Nick Tsao and Nikhil Behari and Akshat Dave and Adithya Pediredla and Ramesh Raskar},
    title = {{Seeing Around Corners in Real-Time using Mobile LiDAR}},
    year = {2025},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/camera-culture/cc-demos}},
}