Eulerian Single-Photon Vision

Shantanu Gupta, Mohit Gupta; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 10465-10476


Single-photon sensors measure light signals at the finest possible resolution -- individual photons. These sensors introduce two major challenges in the form of strong Poisson noise and extremely large data acquisition rates, which are also inherited by downstream computer vision tasks. Previous work has largely focused on solving the image reconstruction problem first and then using off-the-shelf methods for downstream tasks, but the most general solutions that account for motion are costly and not scalable to large data volumes produced by single-photon sensors. This work forgoes the image reconstruction problem. Instead, we demonstrate computationally light-weight phase-based algorithms for the tasks of edge detection and motion estimation. These methods directly process the raw single-photon data as a 3D volume with a bank of velocity-tuned filters, achieving speed-ups of more than two orders of magnitude compared to explicit reconstruction-based methods. Project webpage:

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@InProceedings{Gupta_2023_ICCV, author = {Gupta, Shantanu and Gupta, Mohit}, title = {Eulerian Single-Photon Vision}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2023}, pages = {10465-10476} }