Weak Light as Structural Evidence: Relay-State Hierarchical Representation Learning for Hidden-Screen Reconstruction

We investigate whether an ordinary camera can recover hidden display content from the weak light that the display projects onto a visible relay wall while direct viewing is blocked. Diffuse reflection, spatial spread, and propagation attenuation disperse and mix the brightness, edges, and spatial relations of screen structures, so the wall response carries these cues in a rearranged form. We present Relay-State Hierarchical Representation Learning (RSHRL), a two-pass framework that first organizes this structural evidence through Relay-Wall Invertibility Representation (RWIR) and then repairs residual damage through Damage-State Learning (DSL). RWIR rebuilds wall-to-screen structural correspondence by combining fine evidence, regional relationships, and coarse screen context. DSL estimates spatial and channel damage states from the preliminary reconstruction and its associated features; the second-pass consumer uses these states through its internal DACA, DASA, and SDR operations to refine the affected structures. Experiments on four paired screen-content datasets show that RSHRL leads the evaluated restoration baselines across all 12 PSNR, SSIM, and LPIPS comparisons. Removal and replacement studies demonstrate the complementary value of hierarchical representation and damage-guided repair. Across two acquisition setups and varied observation conditions, the reconstructions recover principal brightness distributions, text-bearing regions, icon contours, window boundaries, and overall interface layouts. These results establish the initial feasibility of recovering hidden screen content with an ordinary camera by observing only wall-reflected display light.