CoRER: Coherent Relay Evidence Restoration for Initial Hidden-Human Contour Observation in Corner-Occluded Scenes

Corner occlusion completely hides a person from direct view, while a visible relay wall carries weak reflected light from the hidden person. We study whether an RGB relay-wall spot image captured by an ordinary camera supports an initial observation of the hidden person's basic region and main contour. The task is challenging because local wall appearance dominates target-associated variation after diffuse relay transport, and contour support is distributed across decoder scales. We present the Coherent Relay Evidence Restoration Model (CoRER), whose Relay Diffuse-Coherent Representation (RDCR) organizes weak front-end evidence with projected local features, scale-separated smoothing, disagreement cues, and a bounded residual update. Its Scale-Coherent Relay-State Restoration (SCRR) measures smooth and detail agreement at decoder skip fusions, organizes multiscale support and reliability, and recalibrates preliminary foreground-background logits to restore the main contour. An explicit positional calibration supplies a bounded shape prior before the final argmax readout. Extensive comparisons, ablation studies, robustness evaluations, and qualitative results validate CoRER's ability to recover the hidden person's basic region and main contour from faint reflected-light spots on the relay wall. Across four real corner scenes in the ReflectHuman benchmark involving different people, corner structures, illumination conditions, and scene settings, CoRER outperforms representative hidden-scene perception and image segmentation methods overall and recovers the basic region and main contour from faint reflected-light spots on the relay wall captured by an ordinary camera, demonstrating the feasibility of this initial contour observation.