SP-TransientBench: A Real-Captured Single Photon Perception Benchmark
Not on the map. Why?
Abstract (arXiv)
Single-photon LiDAR (SPL) based on single-photon avalanche diode (SPAD) sensing enables time-resolved photon measurements with extreme sensitivity, offering unique potential for active 3D perception in photon-starved scenarios.However, real-world single photon perception remains fundamentally challenging due to unique measurement noise and complex multi-return transient phenomena, which jointly complicate geometric reconstruction and semantic scene understanding. Despite growing interest in SPAD-based sensing, existing studies are largely limited to simulated data or small-scale controlled captures. As a result, systematic evaluation of real-world single photon perception across depth estimation, multi-view reconstruction, and 3D semantic understanding remains underexplored. To bridge this gap, we introduce SP-TransientBench (STB), a real-captured multi-task benchmark for single photon perception. SP-TransientBenc comprises 10 diverse scenes and 10,297 views captured using a solid-state single-photon LiDAR at 256×192 resolution. Each view provides full time-of-flight histograms with multi-return behavior,standardized metadata, and calibrated camera poses for multi-view evaluation. We further provide 13-class 3D semantic annotations for selected scenes. By providing dedicated data splits and evaluation protocols for each task, STB enables consistent and reproducible benchmarking of real-world single photon perception across multiple 3D vision problems. The dataset and code will be released upon acceptance.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 16 of its 44 references that are in the map. First posted on arXiv 16 Jun 2026.
Builds on
16 of 44 references.
References · 16
- 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
- 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,088
- 2020Point Transformercited by 1,462
- 2022PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategiescited by 432
- 2022Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Frameworkcited by 376
- 2021T"oRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesiscited by 88
- 2023Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstructioncited by 18
- 2018Dead Time Compensation for High-Flux Rangingcited by 9
- 2024Enhancing Autonomous Navigation by Imaging Hidden Objects using Single-Photon LiDARcited by 8
- 2019Single-photon computational 3D imaging at 45 kmcited by 7
- 2021High-speed object detection with a single-photon time-of-flight image sensorcited by 7
- 2024Transientangelo: Few-Viewpoint Surface Reconstruction Using Single-Photon Lidarcited by 6
4 more
- 2022Robust photon-efficient imaging using a pixel-wise residual shrinkage networkcited by 4
- 2024Time-Resolved MNIST Dataset for Single-Photon Recognitioncited by 4
- 2025Robust 3D Object Detection using Probabilistic Point Clouds from Single-Photon LiDARscited by 3
- 2016A Bayesian approach to denoising of single-photon binary imagescited by 2
Built on by
Not cited yet.