Perceive Once, Decide Per Query: CogVis Splits Change Detection by Decision Scope
TL;DR for operators When the same before-and-after imagery must answer several semantic questions, rerunning the full visual analysis for every query wastes computation that does not actually depend on the query. CogVis separates those decisions by scope. It computes category-independent temporal change evidence once, then repeats only the semantic calibration and candidate verification that must depend on the requested category. The paper reports 28.50% higher inference throughput than the next-fastest compared method; with 10 queries, CogVis takes 10.03 seconds versus 12.56–956.60 seconds for the category-wise baselines evaluated. ...