Temporal Geometry Consistency for Local Structural Drift Verification in Generated Videos

We study local structural drift in generated videos using predicted geometry. We introduce Temporal-Geometry Consistency (TGC), a cohort-relative score that combines four structural and directional-temporal readouts of predicted normals and depth through within-generator ranks. The factors capture temporal directional consistency of the geometry and relation fields, spatial structure in semantic-geometry agreement, and normal-direction consistency from an independent video-depth estimate. On the method-held-out GeneVA 407 set, TGC improves discrimination over the Relation baseline by +0.0367 AUROC under equal-generator, cluster-aware paired inference, with a 95% confidence interval of [+0.0040, +0.0693]. Direct agreement-based normal/depth rerankers do not improve over Relation, while matched-encoding diagnostics show that their agreement-amplitude readout is more sensitive to the tested encodings than the selected structural and directional-temporal summaries. TGC remains cohort-relative: it needs generator identity and a reference cohort. Its appearance-control non-inferiority guardrail is unresolved, so we present TGC as a candidate ranking verifier for local drift, not a calibrated or deployable score.