Plausibility Is Not Quality: Observability-Aware Optical Evidence for Surveillance Image Assessment

Generative models now synthesize surveillance frames that are sharper than authentic footage yet depict scenes that could not physically occur, with reflections lacking sources and shadows lacking objects. Image quality assessment offers no protection because these frames are not degraded, and we show that perceptual quality and perceived plausibility are dissociable perceptual axes. A third property, observability, governs both, since a shadow may be cast by an object outside the frame, so an assessor must distinguish an observed violation from insufficient evidence. We formalize plausibility as the Perceived Plausibility Score (PPS), a continuous human-anchored measure whose protocol also records whether each optical cue was judged decidable, and we construct GenCQA-DB, approximately 55,000 source-grouped authentic and generated CCTV images with controlled reflection, shadow, and illumination violations. We propose PACT, a Physical and Appearance Cross-map Transformer that pairs each optical residual map with a cue confidence map encoding evidence availability and fuses them with appearance entropy maps through cross-map attention. PACT attains an SRCC of 0.874 against 0.791 for an equally supervised image baseline under camera-disjoint evaluation, retains 0.836 when cameras and generator are both held out, and follows human judgments when the evidence for a violation fades instead of mistaking a vanished residual for a consistent scene.