Lumen: Latent Uncertainty-Modulated Evidence Network for Seeing People Around Corners with an Ordinary Camera and Steady Flashlight Illumination

Observing a person beyond an L-shaped corner with an ordinary camera and steady flashlight illumination could support inspection and rescue before direct entry. We study reconstruction of the hidden person from the RGB light pattern recorded on the visible wall. The flashlight–wall–person–wall–camera path contains three diffuse reflections that attenuate and spatially mix body cues with wall background and noise; different body arrangements can also produce similar steady patterns, making coherent reconstruction ambiguous. We propose LUMEN, whose Path-Aware Calibrated Evidence Routing (PACER) estimates relative cue support and routes multiscale evidence, while Evidence-Conditioned Hypothesis Optimization (ECHO) couples global structure selection with progressive refinement. In the extreme L-shaped corner scene where the wall and right-angle turn block the direct view of a person and the camera sees only a wall light pattern from the observation side, using only an ordinary camera and steady flashlight illumination, LUMEN estimates the relative reliability of wall clues from the attenuation and mixing caused by three diffuse reflections, routes evidence across scales, and conditions global selection and progressive refinement of structural hypotheses on this evidence to reconstruct and observe a clear person from extremely weak wall-light information mixed with substantial noise. Across four datasets, LUMEN achieves this goal with higher reconstruction quality than all compared benchmarks and baselines. LUMEN initially enables observation of a target behind a wall using only flashlight illumination. This demonstrates the feasibility of observing a target behind a wall using only flashlight illumination.