SP-TransientBench: A Real-Captured Single Photon Perception Benchmark

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. 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 smallscale 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 multitask benchmark for single photon perception. STB provides 256 × 192 transient data for three tasks: 10 depth estimation samples, 9 reconstruction scenes, and 27 semantic sequences with 10,297 samples. 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 and histogram-domain multi-return annotations for selected scenes, enabling the study of raw transient cues. 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 are available at: https: //huggingface.co/datasets/shuinb/SP-TransientBench